The present study investigated whether individual differences between psychologists in thinking styles are associated with accuracy in diagnostic classification. We asked novice and experienced clinicians to classify two clinical cases of clients with two co-occurring psychological disorders. No significant difference in diagnostic accuracy was found between the two groups, but when combining the data from novices and experienced psychologists accuracy was found to be negatively associated with certain decision making strategies and with a higher self-assessed ability and (...) preference for a rational thinking style. Our results underscore the idea that it might be fruitful to look for explanations of differences in the accuracy of diagnostic judgments in individual differences between psychologists (such as in thinking styles or decision making strategies used), rather than in experience level. (shrink)

This main article for a Philosophy, Psychiatry, & Psychology philosophical case conference is intended to raise philosophical, psychiatric, and public policy issues concerning the relationship between concepts of criminality, mental disorder, and the classification of mental disorders. After introducing the basic problem of the confounding of “vice” and mental disorder concepts in the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition—Text Revision, the author summarizes three different cases from the literature that illustrate the problem of the vice–mental (...) disorder relationship. Four general aspects of the conceptual issues are presented to frame the discussion, and general questions in a range of domains are posed for commentators. (shrink)

Longitudinal diagnostic classification models (DCMs) with hierarchical attributes can characterize learning trajectories in terms of the transition between attribute profiles for formative assessment. A longitudinal DCM for hierarchical attributes was proposed by imposing model constraints on the transition DCM. To facilitate the applications of longitudinal DCMs, this paper explored the critical topic of the Q-matrix design with a simulation study. The results suggest that including the transpose of the R-matrix in the Q-matrix improved the classification accuracy; ten-item (...) tests measuring three linear attributes across three time points provided satisfactory classification accuracy for low-stakes assessment. Educational implications and future directions were discussed. (shrink)

Selected response items and constructed response items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses. Recent research suggests, however, that more information may be available from the CR items than just scores for correctness. In this study, we describe an approach in which a statistical topic model along with a diagnostic classification model was applied to a mixed item format (...) formative test of English and Language Arts. The DCM was used to estimate students’ mastery status of reading skills. These mastery statuses were then included in a topic model as covariates to predict students’ use of each of the latent topics in their written answers to a CR item. This approach enabled investigation of the effects of mastery status of reading skills on writing patterns. Results indicated that one of the skills, Integration of Knowledge and Ideas, helped detect and explain students’ writing patterns with respect to students’ use of individual topics. (shrink)

The purpose of cognitive diagnostic modeling is to classify students' latent attribute profiles using their responses to the diagnostic assessment. In recent years, each diagnostic classification model makes different assumptions about the relationship between a student's response pattern and attribute profile. The previous research studies showed that the inappropriate DCMs and inaccurate Q-matrix impact diagnostic classification accuracy. Artificial Neural Networks have been proposed as a promising approach to convert a pattern of item responses into (...) a diagnostic classification in some research studies. However, the ANNs methods produced very unstable and unappreciated estimation unless a great deal of care was taken. In this research, we combined ANNs with two typical DCMs, the deterministic-input, noisy, “and” gate model and the deterministic-inputs, noisy, “or” gate model, within a semi-supervised learning framework to achieve a robust and accurate classification. In both simulated study and real data study, the experimental results showed that the proposed method could achieve appreciated performance across different test conditions, especially when the diagnostic quality of assessment was not high and the Q-matrix contained misspecified elements. This research study is the first time of applying the thinking of semi-supervised learning into CDM. Also, we used the validating test to choose the appropriate parameters for the ANNs instead of using typical statistical criteria. (shrink)

Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs. Effects were evaluated using bias and RMSE computed between true parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test (...) length. Recovery of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models. (shrink)

The object of this study is the legal framework for the sale or purchase of company shares when the goal of the transaction is the sale of a business. The impact of such transactions on Lithuanian economic development underlines the importance of this study. The recent wave of mergers and acquisitions in Lithuania is likely to substantially increase the number of related legal disputes as well. Legislation on the purchase and sale of company shares and the resulting transfer of business (...) has been enacted in Lithuania only recently. The regulation of such cases remains rather unclear, few cases have been brought to court, and the topic has been barely addressed by legal scholarship in Lithuania to date. It is unclear whether the fact that the real purpose of the transaction is not a simple reassignment of company shares, but business transfer, results in any differences in the interpretation and application of the law. An especially delicate question, raised in Lithuania and other European countries, is whether the buyer may submit a warranty claim to the seller regarding the business acquired. (shrink)

Recent studies indicate a role of the sympathetic nervous system in acute and chronic pain. However, the terminology of the clinical sympathetically maintained pain (SMP) syndromes continues to be confusing and the criteria for diagnosis of SMP are being refined. (blumberg et al.) Despite significant progress in recent years, the mechanisms of the interaction between the sympathetic and sensory systems in SMP remain puzzling.

Diagnosing the Diagnostic and Statistical Manual of Mental Disorders (Karnac, 2014) evaluates the latest edition of the D.S.M.The publication of D.S.M-5 in 2013 brought many changes. Diagnosing the Diagnostic and Statistical Manual of Mental Disorders asks whether the D.S.M.-5 classifies the right people in the right way. It is aimed at patients, mental health professionals, and academics with an interest in mental health. Issues addressed include: How is the D.S.M. affected by financial links with the pharmaceutical industry? To (...) what extent were and should patients involved in revising the classification? How are diagnoses added to the D.S.M.? Does medicalization threaten the idea that anyone is normal? What happens when changes to diagnostic criteria mean that people lose their diagnoses? How important will the D.S.M. be in the future? (shrink)

In psychiatry some disorders of cognition are distinguished from instances of normal cognitive functioning and from other disorders in virtue of their surface features rather than in virtue of the underlying mechanisms responsible for their occurrence. Aetiological considerations often cannot play a significant classificatory and diagnostic role, because there is no sufficient knowledge or consensus about the causal history of many psychiatric disorders. Moreover, it is not always possible to uniquely identify a pathological behaviour as the symptom of a (...) certain disorder, as disorders that are likely to differ both in their causal histories and in their overall manifestations may give rise to very similar patterns of behaviour. -/- Consider delusions as an example. It wouldn’t be correct to define delusions as those beliefs people form as a result of a neurobiological deficit and a hypothesis-evaluation deficit (as some versions of the two-factor theory of delusions suggest), because for some delusions no neurobiological deficit may be found, and reasoning biases and motivational factors may be contributors to the formation of the delusion (e.g. McKay et al., 2005). Moreover, it would be a mistake to define delusions as symptoms of schizophrenia alone, because they occur also in other disorders, including dementia, amnesia, and delusional disorders. Thus, aetiological considerations may appear in the description and analysis of delusions, but do not feature prominently in their definition. -/- In this paper I argue that the surface features used as criteria for the classification and diagnosis of disorders of cognition are often epistemic in character. I shall offer two examples: confabulations and delusions are defined as beliefs or narratives that fail to meet standards of accuracy and justification. Although classifications and diagnoses based on features of people’s observable behaviour are necessary at these early stages of neuropsychiatric research, given the variety of conditions in which certain phenomena appear, I shall attempt to show that current epistemic accounts of confabulations and delusions have limitations. Epistemic criteria can guide both research and clinical practice, but fail to provide sufficient conditions for the identification of delusions and confabulations, and fail to demarcate pathological from non-pathological narratives or beliefs. -/- Another limitation of current epistemic accounts – which I shall not address here – is the excessive focus on epistemic faults of confabulations and delusions at the expense of their epistemically neutral or advantageous features (see Bortolotti and Cox, 2009). This may lead to a misconception of delusions and confabulations, and to an oversimplification in the assessment of the needs of people who require clinical treatment for their psychotic symptoms. (shrink)

Aims: The Research Diagnostic Criteria for Temporomandi¬bular Disorders (RDC/TMD) Axis I diagnostic algorithms were demonstrated to be reliable but below target sensitivity and specificity. Empirical data supported Axis I algorithm revisions that were valid. Axis II instruments were shown to be both reliable and valid. An international consensus workshop was convened to obtain recommendations and finalization of new Axis I diagnostic algorithms and new Axis II instruments. Methods: A comprehensive search of published TMD diagnostic literature was (...) followed by review and consensus via a formal structured process by a panel of experts for revision of the RDC/TMD. Results: The recommended Diagnostic Criteria for TMD (DC/TMD) Axis I protocol includes both a valid screener for pain diagnoses and valid criteria for the most common pain-related TMDs and for one intra-articular disorder. The Axis II protocol retains selected RDC/TMD screening instruments augmented with new instruments to better assess the interactions between pain and psychosocial functioning. A comprehensive classification system is also presented. Conclusion: The recommended evidence-based DC/TMD protocol is appropriate for use in both the clinical and research settings. Simple Axis I and II screening tests augmented by validated Axis I and Axis II instruments allow for identification of simple to complex TMD patients. (shrink)

In this chapter, I provide an overview of phenomenological approaches to psychiatric classification. My aim is to encourage and facilitate philosophical debate over the best ways to classify psychiatric disorders. First, I articulate phenomenological critiques of the dominant approach to classification and diagnosis—i.e., the operational approach employed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-10). Second, I describe the type or typification approach to psychiatric classification, which (...) I distinguish into three different versions: ideal types, essential types, and prototypes. I argue that despite their occasional conflation in the contemporary literature, there are important distinctions among these approaches. Third, I outline a new phenomenological-dimensional approach. I show how this approach, which starts from basic dimensions of human existence, allows us to investigate the full range of psychopathological conditions without accepting the validity of current diagnostic categories. (shrink)

Classifying Madness (Springer, 2005) concerns philosophical problems with the Diagnostic and Statistical Manual of Mental Disorders, more commonly known as the D.S.M. The D.S.M. is published by the American Psychiatric Association and aims to list and describe all mental disorders. The first half of Classifying Madness asks whether the project of constructing a classification of mental disorders that reflects natural distinctions makes sense. Chapters examine the nature of mental illness, and also consider whether mental disorders fall into natural (...) kinds. The second half of the book addresses epistemic worries. Even supposing a natural classification system to be possible in principle, there may be reasons to be suspicious of the categories included in the D.S.M. I examine the extent to which the D.S.M. depends on psychiatric theory, and look at how it has been shaped by social and financial factors. I aim to be critical of the D.S.M. without being antagonistic towards it. Ultimately, however, I am forced to conclude that although the D.S.M. is of immense practical importance, it is unlikely to come to reflect the natural structure of mental disorders. (shrink)

A significant portion of the scholarship in analytic philosophy of psychiatry has been devoted to the problem of what kind of kind psychiatric disorders are. Efforts have included descriptive projects, which aim to identify what psychiatrists in fact refer to when they diagnose, and prescriptive ones, which argue over that to which diagnostic categories should refer. In other words, philosophers have occupied themselves with what I call “diagnostic kinds”. However, the pride of place traditionally given to diagnostic (...) kinds in psychiatric research has recently come under attack, most notably by a recent initiative of the National Institute of Mental Health, the Research Domain Criteria Project, that seeks to exclude diagnostic categories from experimental designs and focus on other sorts of psychiatric kinds. I argue that philosophical accounts privileging diagnostic kinds must respond to this new line of criticism, and conclude that philosophers need to either counter psychiatrists’ growing suspicion about the hegemony of diagnostic categories in the clinic and the laboratory, or join in redirecting their efforts toward the development of robust accounts of other sorts of psychiatric objects and processes. (shrink)

This paper addresses philosophical issues concerning whether mental disorders are natural kinds and how the DSM should classify mental disorders. I argue that some mental disorders (e.g., schizophrenia, depression) are natural kinds in the sense that they are natural classes constituted by a set of stable biological mechanisms. I subsequently argue that a theoretical and causal approach to classification would provide a superior method for classifying natural kinds than the purely descriptive approach adopted by the DSM since DSM-III. My (...) argument suggests that the DSM should classify natural kinds in order to provide predictively useful (i.e., projectable) diagnostic categories and that a causal approach to classification would provide a more promising method for formulating valid diagnostic categories. (shrink)

Preoperative diagnosis of gastric cancer and primary gastric lymphoma is challenging and has important clinical significance. Inspired by the inductive reasoning learning of the human brain, transfer learning can improve diagnosis performance of target task by utilizing the knowledge learned from the other domains (source domain). However, most studies focus on single-source transfer learning and may lead to model performance degradation when a large domain shift exists between the single-source domain and target domain. By simulating the multi-modal information learning and (...) transfer mechanism of human brain, this study designed a multisource transfer learning feature extraction and classification framework, which can enhance the prediction performance of the target model by using multisource medical data (domain). First, this manuscript designs a feature extraction network that takes the maximum mean difference based on the Wasserstein distance as an adaptive measure of probability distribution and extracts the domain-specific invariant representations between source and target domain data. Then, aiming at the random generation of parameters bringing uncertainties to prediction accuracy and generalization ability of extreme learning machine network, the 1-norm regularization is used to implement sparse constraints of the output weight matrix and improve the robustness of the model. Finally, some experiments are carried out on the data of two medical centers. The experimental results show that the area under curves (AUCs) of the method are 0.958 and 0.929 in the two validation cohorts, respectively. The method in this manuscript can provide doctors with a better diagnostic reference, which has certain practical significance. (shrink)

This article supports calls for an increased integration of patients into taxonomic decision making in psychiatry by arguing that their exclusion constitutes a special kind of epistemic injustice: preemptive testimonial injustice, which precludes the opportunity for testimony due to a wrongly presumed irrelevance or lack of expertise. Here, this presumption is misguided for two reasons: the role of values in psychiatric classification and the potential function of first-person knowledge as a corrective means against implicitly value-laden, inaccurate, or incomplete (...) class='Hi'>diagnostic criteria sets. This kind of epistemic injustice leads to preventable epistemic losses in psychiatric classification, diagnosis, and treatment. (shrink)

This chapter examines philosophical issues surrounding the classification of mental disorders by the Diagnostic and Statistical Manual of Mental Disorders (DSM). In particular, the chapter focuses on issues concerning the relative merits of descriptive versus theoretical approaches to psychiatric classification and whether the DSM should classify natural kinds. These issues are presented with reference to the history of the DSM, which has been published regularly by the American Psychiatric Association since 1952 and is currently in its fifth (...) edition. While the first two editions of the DSM adopted a theoretical (psychoanalytic) and etiological approach to classification, subsequent editions of the DSM have adopted an atheoretical and purely descriptive (“neo-Kraepelinian”) approach. It is argued that largest problem with the DSM at present—viz., its failure to provide valid diagnostic categories—is directly related to the purely descriptive methodology championed by the DSM since the third edition of the DSM. In light of this problem, the chapter discusses the prospects of a theoretical and causal approach to psychiatric classification and critically examines the assumption that the DSM should classify natural kinds. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Deflating Psychiatric ClassificationClaudio E. M. Banzato (bio)Keywordsnosography, comorbidity, utility, pragmatismSystems of classification bring order into the world. They are a key part of the informational working infrastructure of the world we inhabit (Bowker and Star 1999). Thus, much of the human interaction hinges on these ordering—pattern identifying and creating—systems. Formal or informal, standardized or ad hoc, visible or invisible, enforced or optional, there are a myriad of classifications (...) we necessarily live by.Typically, classifications convey representations of states of affairs to make interventions on them feasible and, to some extent, predictable. In other words, classificatory systems and schemes try to confer intelligibility to the world. By succeeding in such task, they may provide rational grounds to human operation on reality (toward the most diverse ends). This account fully applies to medical classifications, which struggle to sort out all kinds of diseases, ailments, complaints, and sufferings that can possibly be targeted by medical interventions. This means classifications are instrumental to the ends pursued by medicine, quintessential modificatory activity. In sum, classifications are cognitive tools devised to build up knowledge by making relevant distinctions, which may prove helpful to guide human action.By working well, classifications eventually tend to become invisible. They end up looking just natural, as if they were carved by nature itself. But indeed purpose is the touchstone here. Even if a given class of objects fully qualifies as a 'natural kind' and necessary and sufficient criteria for class membership can be definitely established, it does not entail that it constitutes the best way to classify these objects irrespective of the context. Peter Zachar (2002) offers a compelling example from natural sciences, the utmost practical importance of distinguishing between hydrogen and its isotopes (hydrogen, deuterium, and tritium). In this case, the classificatory thrust stretches beyond the shared atomic number. In his words, "A crucial factor in recognizing them as distinct is that they are used in distinct activities and practices. We get a better neutron bounce with heavy water or D2O. Deciding what aspects of internal structure are important therefore cannot be isolated from external factors." (p. 220)In contemporary psychiatry, diagnostic classification has been center stage for several reasons. But before addressing them, however, a brief historical detour is necessary. Back in the nineteenth century, putting forward a new classification of mental diseases was taken somewhat as a token of psychiatric proficiency according to the witty remark by the French physician and publicist Philippe Buchez: "Upon believing that they have [End Page 23] completed their studies, rhetoricians will compose a tragedy and alienists a classification" (Berrios 1999, 152). By the middle of the twentieth century, many psychiatric classifications (based on diverse principles and underlying theoretical orientations) were still used across the world. The British psychiatrist Erwin Stengel (1959), in his influential report on classification of mental disorders, pointed out that the issue of difficulty of communication was then the order of the day for psychiatry, because it was widely perceived as one of the most serious obstacles to the progress in the field.The broad, worldwide survey carried out by Stengel made it clear that classifications of all shapes were used in different contexts, but they were seldom appealing outside the boundaries of the respective centers that generated them. Such diversity of classifications reflected not only different functions or purposes they were meant to serve, but also the role played by the history of a given problem within a particular medical tradition and cultural background. Thus, Stengel's aims for an acceptable statistical international classification were relatively modest: it should simply ground epidemiological work.Stengel's stance on classification was frankly pragmatic and utilitarian. He understood well the difficulties posed by the 'disease entity' assumption in psychiatry and asked the straight question: "Firstly, what do we classify in this field? Are we classifying diseases or people?", to which he offered a compromised answer: "It may be said that the material the psychiatrist has to classify consists neither of diseases nor of people but of a variety of disorders or reactions, a material which does not readily lend itself to classification" (Stengel 1959, 612). For him, the pursued agreement on the... (shrink)

A large part of the controversy surrounding the publication of DSM-5 stems from the possibility of replacing the purely descriptive approach to classification favored by the DSM since 1980. This paper examines the question of how mental disorders should be classified, focusing on the issue of whether the DSM should adopt a purely descriptive or theoretical approach. I argue that the DSM should replace its purely descriptive approach with a theoretical approach that integrates causal information into the DSM’s descriptive (...) diagnostic categories. The paper proceeds in three sections. In the first section, I examine the goals (viz., guiding treatment, facilitating research, and improving communication) associated with the DSM’s purely descriptive approach. In the second section, I suggest that the DSM’s purely descriptive approach is best suited for improving communication among mental health professionals; however, theoretical approaches would be superior for purposes of treatment and research. In the third section, I outline steps required to move the DSM towards a hybrid system of classification that can accommodate the benefits of descriptive and theoretical approaches, and I discuss how the DSM’s descriptive categories could be revised to incorporate theoretical information regarding the causes of disorders. I argue that the DSM should reconceive of its goals more narrowly such that it functions primarily as an epistemic hub that mediates among various contexts of use in which definitions of mental disorders appear. My analysis emphasizes the importance of pluralism as a methodological means for avoiding theoretical dogmatism and ensuring that the DSM is a reflexive and self-correcting manual. (shrink)

Psychiatric classification, as exemplified by the Diagnostic and Statistical Manual of Mental Disorders, is dealing with a lack of trust and credibility—in the scientific, but also in the public realm. Regarding the latter in particular, one possible remedial measure for this crisis in trust lies in an increased integration of patients into the DSM revision process. The DSM, as a manual for clinical practice, is forced to make decisions that exceed available data and involve value-judgments. Regarding such decisions, (...) public epistemic trustworthiness requires that these value-judgments should be representative of those of the affected public, and that the public has a reason to believe such a representation to be realized. Due to the long tradition of distrust in psychiatry, such a reason can in this case best be provided by an actual integration of patients into the decision-making process, rather than by their representation through scientific experts. (shrink)

A new diagnostic system for organic psychiatry is presented. We first define "organic psychiatry", and then give the theoretical basis for conceiving organic psychiatric disorders in terms of hypothetical psychopathogenetic processes, HPP:s. Such hypothetical disorders are not strictly identical to the clusters of symptoms in which they typically manifest themselves, since the symptoms may be concealed or modified by intervening factors in non typical circumstances and/or in the simultaneous presence of several disorders. The six basic disorders in our system (...) are Astheno Emotional Disorder (AED), Somnolence Sopor Coma Disorder (SSCD), Hallucination Coenestopathy Depersonalisation Disorder (HCDD), Confusional Disorder (CD), Emotional Motivational Blunting Disorder (EMD) and Korsakoff's Amnestic Disorder (KAD). We describe their usual etiologies, their typical symptoms and course, and some forms of interaction between them. (shrink)

Cognitive diagnostic models show great promise in language assessment for providing rich diagnostic information. The lack of a full understanding of second language listening subskills made model selection difficult. In search of optimal CDM that could provide a better understanding of L2 listening subskills and facilitate accurate classification, this study carried a two-layer model selection. At the test level, A-CDM, LLM, and R-RUM had an acceptable and comparable model fit, suggesting mixed inter-attribute relationships of L2 listening subskills. (...) At the item level, Mixed-CDMs were selected and confirmed the existence of mixed relationships. Mixed-CDMs had better model and person fit than G-DNIA. In addition to statistical approaches, the content analysis provided theoretical evidence to confirm and amend the item-level CDMs. It was found that semantic completeness pertaining to the attributes and item features may influence the attribute relationships. Inexplicable attribute conflicts could be a signal of suboptimal model choice. Sample size and the number of multi-attribute items should be taken into account in L2 listening cognitive diagnostic modeling studies. This study provides useful insights into the model selection and the underlying cognitive process for L2 listening tests. (shrink)

A diagnostic judgment of a teacher can be seen as an inference from manifest observable evidence on a student’s behavior to his or her latent traits. This can be described by a Bayesian model of in-ference: The teacher starts from a set of assumptions on the student (hypotheses), with subjective probabilities for each hypothesis (priors). Subsequently, he or she uses observed evidence (stu-dents’ responses to tasks) and knowledge on conditional probabilities of this evidence (likelihoods) to revise these assumptions. Many (...) systematic deviations from this model (biases, e.g. base-rate neglect, inverse fallacy) are reported in literature on Bayesian reasoning. In a teacher’s situation the information (hypotheses, priors, likelihoods) is usually not explicitly represented numerically (as in most research on Bayesian reasoning), but only by qualitative esti-mations in the mind of the teacher. In our study, we ask to which extent individuals (approximately) apply a rational Bayesian strategy or resort on other biased strategies of processing information for their diagnostic judgments. We explicitly pose this question with respect to non-numerical settings. To investigate this question, we developed a scenario that visually displays all relevant information (hypotheses, priors, likelihoods) in a graphically displayed hypothesis space (called “hypothegon”) – without recurring to numerical representations or mathematical procedures. 42 pre-service teach-ers were asked to judge the plausibility of different misconceptions of six students based on their responses to decimal comparison tasks (e.g. 3.39 > 3.4). Applying a Bayesian classification proce-dure, we identified three updating strategies: A Bayesian update strategy (BUS, processing all probabilities), a combined evidence strategy (CES, ignoring the prior probabilities but including all likelihoods), and a single evidence strategy (SES, only using the likelihood of the most probable hypothesis). In study 1, an instruction on the relevance of using all probabilities (priors and likelihoods) only weakly increased the processing of more information. In study 2, we found strong evidence that a visual explication of the prior-likelihood interaction led to an increase of processing the interaction of all relevant information. These results show that the phenomena found in general research on Bayesian reasoning in numerical settings extend to diagnostic judgments in non-numerical settings. (shrink)

Transfer learning can improve the robustness of deep learning in the case of small samples. However, when the semantic difference between the source domain data and the target domain data is large, transfer learning easily introduces redundant features and leads to negative transfer. According the mechanism of the human brain focusing on effective features while ignoring redundant features in recognition tasks, a brain-like classification method based on adaptive feature matching dual-source domain heterogeneous transfer learning is proposed for the preoperative (...) aided diagnosis of lung granuloma and lung adenocarcinoma for patients with solitary pulmonary solid nodule in the case of small samples. The method includes two parts: (1) feature extraction and (2) feature classification. In the feature extraction part, first, By simulating the feature selection mechanism of the human brain in the process of drawing inferences about other cases from one instance, an adaptive selected-based dual-source domain feature matching network is proposed to determine the matching weight of each pair of feature maps and each pair of convolution layers between the two source networks and the target network, respectively. These two weights can, respectively, adaptive select the features in the source network that are conducive to the learning of the target task, and the destination of feature transfer to improve the robustness of the target network. Meanwhile, a target network based on diverse branch block is proposed, which made the target network have different receptive fields and complex paths to further improve the feature expression ability of the target network. Second, the convolution kernel of the target network is used as the feature extractor to extract features. In the feature classification part, an ensemble classifier based on sparse Bayesian extreme learning machine is proposed that can automatically decide how to combine the output of base classifiers to improve the classification performance. Finally, the experimental results (the AUCs were 0.9542 and 0.9356, respectively) on the data of two center data show that this method can provide a better diagnostic reference for doctors. (shrink)

This dissertation examines psychiatry from a philosophy of science perspective, focusing on issues of realism and classification. Questions addressed in the dissertation include: What evidence is there for the reality of mental disorders? Are any mental disorders natural kinds? When are disease explanations of abnormality warranted? How should mental disorders be classified? -/- In addressing issues concerning the reality of mental disorders, I draw on the accounts of realism defended by Ian Hacking and William Wimsatt, arguing that biological research (...) on mental disorders supports the inference that some mental disorders (e.g., schizophrenia, mood disorders, and anxiety disorders) are real theoretical entities, and that the evidence supporting this inference is causal and abductive. In explicating the nature of such entities, I argue that real mental disorders are natural kinds insofar as they are natural classes of abnormal behavior whose members share the same causal structure. I present this position in terms of Richard Boyd’s homeostatic cluster property theory of natural kinds, and argue that this perspective reveals limitations of Hacking’s account on the looping effects of human kinds, which suggests that the objects classified by psychiatrists are unstable entities. I subsequently argue that a subset of mental disorders (e.g., schizophrenia and Down syndrome) are mental illnesses insofar as they are disorders caused by a dysfunctional biological process that leads to harmful consequences for individuals. I present this analysis against Thomas Szasz’s argument that mental illness is a myth. -/- In addressing issues of psychiatric classification, my analysis focuses on the Diagnostic and Statistical Manual of Mental Disorders (DSM), which has been published regularly by the American Psychiatric Association since 1952, and is currently in its fourth edition. After examining the history of DSM in the twentieth century, and in particular, DSM’s shift to an atheoretical and purely descriptive system in the 1980s, I consider the relative merits of descriptive versus causal systems of classification. Drawing on Carl Hempel’s analysis of taxonomic systems in psychiatry, I argue that a causal classification system would provide a superior approach to psychiatric classification than the descriptive system currently favored by DSM. (shrink)

Abstract Recently, some philosophers of psychiatry (viz., Rachel Cooper and Dominic Murphy) have analyzed the issue of psychiatric classification. This paper expands upon these analyses and seeks to demonstrate that a consideration of the history of the Diagnostic and Statistical Manual of Mental Disorders (DSM) can provide a rich and informative philosophical perspective for critically examining the issue of psychiatric classification. This case is intended to demonstrate the importance of history for philosophy of psychiatry, and more generally, (...) the potential benefits of historically-informed approaches to philosophy of science. (shrink)

Medical expert systems (MES) are knowledge-based computer programs that are designed for advising physicians on diagnostical and therapeutical decision-making. They use heuristic methods developed by Artificial Intelligence researchers in order to retrieve from large knowledge-bases information needed in the situation. Constructing the knowledge-base of a MES embraces the problem of explicating and fixing the conceptual, causal and epistemic relations between a lot of medical objects. There is a number of preconditions which any adequate representation of such knowledge must fulfil, among (...) them the conditions of consistency, of completeness, of unequivocality, etc. Existing systems for classification and coding, like ICD and SNOMED, are not designed for the needs of constructing expert systems or, more generally, of knowledge processing and knowledge engineering. Their syntax is not sufficiently rich for expressing the more complex structures of (medical) knowledge. What is needed, is a language that can be used for expressing logical and descriptive relations between medical objects and facts, approximately at the level of the language of second order predicate logic. Simultaneously, it must be possible to process this language at the machine level. This can be achieved by using some dialects of the programming language LISP or, particularly, by using the programming language PROLOG. Thus, in order to achieve a suitable classification system, it is necessary to develop a system of medical data structures and predicates expressed in LISP or PROLOG. (shrink)

B a c k g r o u n d. The article demonstrates the development and influence of the main diagnostic systems in psychiatry, such as the DSM and the ICD, on the concept of psychiatric diseases. The problem of classification of psychiatric disorders is one of the main topics that is the field of study of the philosophy of psychiatry. The correct diagnosis within a particular diagnostic system directly affects the choice of appropriate drug treatment, psychotherapy (...) and social support for people suffering from mental disorders. Misdiagnosis has not only negative medical but also social consequences, leading to stigmatization and avoidance of people suffering from mental disorders. M e t h o d s. The research uses an integrated approach to the analysis of psychiatric diagnostic systems, including historical, comparative and interdisciplinary methods. The application of the historical method contributed to a detailed study of the evolution of psychiatric diagnostic systems and changes in approaches to the classification of mental disorders. A comparative analysis of the main diagnostic systems was carried out, considering their structure, diagnostic criteria and interaction. The interdisciplinary method involves the integration of knowledge from psychiatry, philosophy, medical history, cultural studies, and psychology, providing a deep understanding of the medical, philosophical, social, and cultural aspects of mental disorders. R e s u l t s. The article analyzes the historical development of ideas and methodology for the classification of mental disorders from ancient Greece to the present. From Hippocrates and Plato to Sydenham, Kabanis, Pinel, and Eskierol, the authors trace the evolution of understanding of mental disorders, emphasizing the shift in emphasis from etiological theories to more descriptive and categorical models. The authors describe the current state of the DSM and ICD classification systems, which play a dominant role in psychiatric science and subsequent social support and welfare for people suffering from mental disorders. Changes that have occurred in these systems and their impact on psychiatric practice and research are discussed. Considerable emphasis is placed on the history of the diagnosis of post-traumatic stress disorder (PTSD), which becomes a symbolic indicator of the complexities and challenges associated with the modern classification of mental illness. The authors consider the phenomenological method as a tool for a deeper understanding of PTSD, especially in the context of the constant psychotraumatic factors of war, the consequences of which generate new challenges for Ukrainian psychiatric practice. The authors present a case study using the phenomenological approach to diagnose PTSD, which demonstrates the need for a detailed analysis of patients' internal experience for accurate diagnosis and effective treatment. C o n c l u s i o n s. The conclusions emphasize the importance of integrating philosophical methods into the diagnosis and analysis of mental illness in clinical practice. The authors call for the development of interdisciplinary research involving both philosophers and mental health professionals to develop more detailed and person-centered approaches to the diagnosis and treatment of mental disorders. (shrink)

Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to as the diagnostic assistant tool for screening of cardiac disorder. The research purposes of a cardiac disorder detection system from 12-lead-based ECG Images. The healthcare institutes used various ECG equipment that present results in nonuniform formats of ECG images. The research study proposes a generalized methodology to process all (...) formats of ECG. Single Shoot Detection MobileNet v2-based Deep Neural Network architecture was used to detect cardiovascular disease detection. The study focused on detecting the four major cardiac abnormalities with 98% accuracy results were calculated. The work is relatively rare based on their dataset; a collection of 11,148 standard 12-lead-based ECG images used in this study were manually collected from health care institutes and annotated by the domain experts. The study achieved high accuracy results to differentiate and detect four major cardiac abnormalities. Several cardiologists manually verified the proposed system’s accuracy result and recommended that the proposed system can be used to screen for a cardiac disorder. (shrink)

Contemporary psychiatry finds itself in the midst of a crisis of classification. The developments begun in the 1980s—with the third edition of the Diagnostic and Statistical Manual of Mental Disorders —successfully increased inter-rater reliability. However, these developments have done little to increase the predictive validity of our categories of disorder. A diagnosis based on DSM categories and criteria often fails to accurately anticipate course of illness or treatment response. In addition, there is little evidence that the DSM categories (...) link up with genetic findings, and even less evidence that they... (shrink)

The Diagnostic and Statistical Manual (DSM) of the American Psychiatric Association, currently in its fourth edition and considered the reference for the characterization and diagnosis of mental disorders, has undergone various developments since its inception in the mid-twentieth century. With the fifth edition of the DSM presently in field trials for release in 2013, there is renewed discussion and debate over the extent of its relative successes - and shortcomings - at iteratively incorporating scientific evidence on the often ambiguous (...) nature and etiology of mental illness. Given the power that the DSM has exerted both within psychiatry and society at large, this essay seeks to analyze variations in content and context of various editions of the DSM, address contributory influences and repercussion of such variations on the evolving landscape of psychiatry as discipline and practice over the past sixty years. Specifically, we document major modifications in the definition, characterization, and classification of mental disorders throughout successive editions of the DSM, in light of shifting trends in the conceptualization of psychopathology within evolving schools of thought in psychiatry, and in the context of progress in behavioral and psychopharmacological therapeutics over time. We touch upon the social, political, and financial environments in which these changes took places, address the significance of these changes with respect to the legitimacy (and legitimization) of what constitutes mental illness and health, and examine the impact and implications of these changes on psychiatric practice, research, and teaching. We argue that problematic issues in psychiatry, arguably reflecting the large-scale adoption of the DSM, may be linked to difficulties in formulating a standardized nosology of psychopathology. In this light, we highlight 1) issues relating to attempts to align the DSM with the medical model, with regard to increasing specificity in the characterization of discrete mental disease entities and the incorporation of neurogenetic, neurochemical and neuroimaging data in its nosological framework; 2) controversies surrounding the medicalization of cognition, emotion, and behavior, and the interpretation of subjective variables as 'normal' or 'abnormal' in the context of society and culture; and 3) what constitutes treatment, enablement, or enhancement - and what metrics, guidelines, and policies may need to be established to clarify such criteria. (shrink)

Cognitive diagnostic assessment has been developed rapidly to provide fine-grained diagnostic feedback on students’ subskills and to provide insights on remedial instructions in specific domains. To date, most cognitive diagnostic studies on reading tests have focused on retrofitting a single booklet from a large-scale assessment. Critical issues in CDA involve the scarcity of research to develop diagnostic tests and the lack of reliability and validity evidence. This study explored the development and validation of the Diagnostic (...) Chinese Reading Comprehension Assessment for primary students under the CDA framework. Reading attributes were synthesized based on a literature review, the national curriculum criteria, the results of expert panel judgments, and student think-aloud protocols. Then, the tentative attributes were used to construct three booklets of reading comprehension items for 2–6 graders at three key stages. The assessment was administered to a large population of students in grades 2–6 from 20 schools in a district of Changchun City, China. Q-matrices were compared and refined using the model-data fit and an empirical validation procedure, and five representative cognitive diagnostic models were compared for optimal performance. The fit indices suggested that a six-attribute structure and the G-DINA model were best fitted for the reading comprehension assessment. In addition, diagnostic reliability, construct, internal and external validity results were provided, supporting CDM classifications as reliable, accurate, and useful. Such diagnostic information could be utilized by students, teachers, and administrators of reading programs and instructions. (shrink)

Forensic evidence often involves an evaluation of whether two impressions were made by the same source, such as whether a fingerprint from a crime scene has detail in agreement with an impression taken from a suspect. Human experts currently outperform computer-based comparison systems, but the strength of the evidence exemplified by the observed detail in agreement must be evaluated against the possibility that some other individual may have created the crime scene impression. Therefore, the strongest evidence comes from features in (...) agreement that are also not shared with other impressions from other individuals. We characterize the nature of human expertise by applying two extant metrics to the images used in a fingerprint recognition task and use eye gaze data from experts to both tune and validate the models. The Attention via Information Maximization model quantifies the rarity of regions in the fingerprints to determine diagnosticity for purposes of excluding alternative sources. The CoVar model captures relationships between low-level features, mimicking properties of the early visual system. Both models produced classification and generalization performance in the 75%–80% range when classifying where experts tend to look. A validation study using regions identified by the AIM model as diagnostic demonstrates that human experts perform better when given regions of high diagnosticity. The computational nature of the metrics may help guard against wrongful convictions, as well as provide a quantitative measure of the strength of evidence in casework. (shrink)

Multiple studies show that periodic reanalysis of genomic test results held by clinical laboratories delivers significant increases in overall diagnostic yield. However, while there is a widespread consensus that implementing routine reanalysis procedures is highly desirable, there is an equally widespread understanding that routine reanalysis of individual patient results is not presently feasible to perform for all patients. Instead, researchers, geneticists and ethicists are beginning to turn their attention to one part of reanalysis—reinterpretation of previously classified variants—as a means (...) of achieving similar ends to large-scale individual reanalysis but in a more sustainable manner. This has led some to ask whether the responsible implementation of genomics in healthcare requires that diagnostic laboratories routinely reinterpret their genomic variant classifications and reissue patient reports in the case of materially relevant changes. In this paper, we set out the nature and scope of any such obligation, and analyse some of the main ethical considerations pertaining to a putative duty to reinterpret. We discern and assess three potential outcomes of reinterpretation—upgrades, downgrades and regrades—in light of ongoing duties of care, systemic error risks and diagnostic equity. We argue against the existence of any general duty to reinterpret genomic variant classifications, yet we contend that a suitably restricted duty to reinterpret ought to be recognised, and that the responsible implementation of genomics into healthcare must take this into account. (shrink)

This thesis investigates the nature of psychiatric disorders, and to what extent they can form a basis for classification, explanation, and treatment interventions. These questions are important in the light of the “crisis of validity” in psychiatry, according to which current diagnostic categories do not pick out real disorders. I address the questions by defending an account of psychiatric disorders that can better accommodate social aspects and non-epistemic values than the symptom-based model of the Diagnostic and Statistical (...) Manual of Mental Disorders (DSM) and the brain disease model of the biomedical approach, including the Research Domain Criteria (RDoC). I concentrate on three ways that psychiatric disorders can differ from prototypical natural kinds, such as biological species and chemical elements. First, the concept of psychiatric disorder or mental disorder is partly value-laden and cannot be defined based only on scientific facts. Second, the objects of psychiatric classifications are interactive human kinds because people with disorders respond to their classifications through looping effects. Third, sociocultural factors can shape disorders in complex ways, which is indicated by their cross-cultural variation. I argue that these challenges can be overcome with a pluralistic explanatory account that grants an explicit role to value-sensitive considerations and social scientific research. Based on this, I argue that particular disorders can in principle support inductive inferences. ------------------------------------------------------------------------------------------ My key argument is that although whether a condition is considered pathological is partly a value-laden question, this does not rule out a realist account of particular psychiatric disorders as homeostatic property cluster kinds (HPC). I assert that causal mechanisms responsible for psychiatric kinds can be understood non-metaphysically based on the contrastive-counterfactual and interventionist theories of explanation. An advantage of this account is that it can address the concern that psychiatric explanations require one to relate heterogeneous causal factors on different levels, such as genetic, neurological, psychological, and social. My novel argument is that mechanistic explanations of scientific kinds have applicability domains over which they account for specific aspects of kinds and warrant inductive inferences. That is, identifying the applicability domain of an explanation spells out the conditions under which the explanation is expected to be reliable and when it can break down. This helps to understand how different discipline approaches, including social and cultural ones, can be complementary and make an explanation of a psychiatric kind more reliable. On the other hand, the account also shows how the complex nature of psychiatric kinds can license re-classifications for different epistemic and non-epistemic purposes. Finally, in the light of the social implications of psychiatric classifications, I suggest a value-sensitive or ameliorative approach to engineering the concept of psychiatric disorder. In conclusion, my account shows that research on the social and cultural factors that shape psychiatric disorders, and weighing the non-epistemic values that influence classificatory practices, can and should inform classificatory choices as well as policy and treatment interventions. (shrink)

Multi-level teaching has been proven to be more effective than a one-size-fits-all learning approach. This study aimed to develop and implement a multi-level remedial teaching scheme in various high school classes containing students of a wide range of learning levels and to determine its effect of their learning. The deterministic inputs noisy and gate model of cognitive diagnosis theory was used to classify students at multiple levels according to their knowledge and desired learning outcomes. A total of 680 senior high (...) school students from central provinces in China participated in the initial cognitive diagnostic test, and 1,615 high school sophomores from seven high schools in China participated in a formal cognitive diagnosis test. Thirty-six high school students from Southwestern China participated in the think-aloud protocols, and 258 seniors from three high schools in southwest China participated in the remedial teaching experiment. Through an analysis of students’ think-aloud protocols, cognitive errors of students at all levels were determined, and multi-level remedial teaching programs were designed to address these common cognitive errors. The remedial teaching programs were then implemented in three schools and compared with a control group. The results indicated that the students in the experimental group showed a more significant improvement. In this study, the steps of designing multi-level remedial teaching include assessment, classification, and preparing a teaching scheme, which are feasible and can have remarkable teaching effects. This process can be used for reference by teachers of various subjects. (shrink)

The ongoing coronavirus 2019 pandemic caused by the severe acute respiratory syndrome coronavirus 2 has resulted in a severe ramification on the global healthcare system, principally because of its easy transmission and the extended period of the virus survival on contaminated surfaces. With the advances in computer-aided diagnosis and artificial intelligence, this paper presents the application of deep learning and adversarial network for the automatic identification of COVID-19 pneumonia in computed tomography scans of the lungs. The complexity and time limitation (...) of the reverse transcription-polymerase chain reaction swab test makes it disadvantageous to depend solely on as COVID-19’s central diagnostic mechanism. Since CT imaging systems are of low cost and widely available, we demonstrate that the drawback of the RT-PCR can be alleviated with a faster, automated, and reduced contact diagnostic process via the use of a neural network model for the classification of infected and noninfected CT scans. In our proposed model, we explore the benefit of transfer learning as a means of resolving the problem of inadequate dataset and the importance of semisupervised generative adversarial network for the extraction of well-mapped features and generation of image data. Our experimental evaluation indicates that the proposed semisupervised model achieves reliable classification, taking advantage of the reflective loss distance between the real data sample space and the generated data. (shrink)