Extracting Patient Case Profiles with Domain-Specific Semantic Categories

2010 ◽  
pp. 273-287
Author(s):  
Yitao Zhang ◽  
Jon Patrick
Keyword(s):  
Case Studies ◽  
Clinical Case ◽  
Support Vector ◽  
Svm Classifier ◽  
Patient Case ◽  
Semantic Categories ◽  
Domain Specific ◽  
Clinical Case Studies ◽  
Golden Standard ◽  
Domain Specific Knowledge

The fast growing content of online articles of clinical case studies provides a useful source for extracting domain-specific knowledge for improving healthcare systems. However, current studies are more focused on the abstract of a published case study which contains little information about the detailed case profiles of a patient, such as symptoms and signs, and important laboratory test results of the patient from the diagnostic and treatment procedures. This paper proposes a novel category set to cover a wide variety of semantics in the description of clinical case studies which distinguishes each unique patient case. A manually annotated corpus consisting of over 5000 sentences from 75 journal articles of clinical case studies has been created. A sentence classification system which identifies 13 classes of clinically relevant content has been developed. A golden standard for assessing the automatic classifications has been established by manual annotation. A maximum entropy (MaxEnt) classifier is shown to produce better results than a Support Vector Machine (SVM) classifier on the corpus.

Clinical Case Studies in Renal Transplantation

2013 ◽  
Vol 12 (2) ◽  
pp. 75-75
Keyword(s):  
Risk Assessment ◽  
Chronic Kidney Disease ◽  
Pulmonary Hypertension ◽  
Renal Transplantation ◽  
Kidney Disease ◽  
Case Studies ◽  
Clinical Case ◽  
Hemodynamic Evaluation ◽  
Clinical Case Studies

The case studies below are referred to in the articles “Pulmonary Hypertension in Patients with Chronic Kidney Disease: Noninvasive Strategies for Patient Phenotyping and Risk Assessment” by Amresh Raina, MD, and “Hemodynamic Evaluation of Pulmonary Hypertension in Chronic Kidney Disease” by Ryan Tedford, MD, and Paul Forfia, MD, on the following pages.

Clinical Case Studies

2007 ◽  
pp. 59-189
Author(s):  
Luc J. Jordaens ◽  
Dominic A.M.J. Theuns
Keyword(s):  
Case Studies ◽  
Clinical Case ◽  
Clinical Case Studies

Domain-Specific Knowledge Systems in the Brain: The Animate-Inanimate Distinction

1998 ◽  
Vol 10 (1) ◽  
pp. 1-34 ◽  
Author(s):  
Alfonso Caramazza ◽  
Jennifer R. Shelton
Keyword(s):  
Knowledge Systems ◽  
Neural Mechanisms ◽  
Specific Knowledge ◽  
Knowledge Framework ◽  
Semantic Categories ◽  
Domain Specific ◽  
Domain Specific Knowledge ◽  
Cognitive Neuropsychological ◽  
The Brain ◽  
Selective Impairment

We claim that the animate and inanimate conceptual categories represent evolutionarily adapted domain-specific knowledge systems that are subserved by distinct neural mechanisms, thereby allowing for their selective impairment in conditions of brain damage. On this view, (some of) the category-specific deficits that have recently been reported in the cognitive neuropsychological literature—for example, the selective damage or sparing of knowledge about animals—are truly categorical effects. Here, we articulate and defend this thesis against the dominant, reductionist theory of category-specific deficits, which holds that the categorical nature of the deficits is the result of selective damage to noncategorically organized visual or functional semantic subsystems. On the latter view, the sensory/functional dimension provides the fundamental organizing principle of the semantic system. Since, according to the latter theory, sensory and functional properties are differentially important in determining the meaning of the members of different semantic categories, selective damage to the visual or the functional semantic subsystem will result in a category-like deficit. A review of the literature and the results of a new case of category-specific deficit will show that the domain-specific knowledge framework provides a better account of category-specific deficits than the sensory/functional dichotomy theory.

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