Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier
Objective: Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This can be further facilitated if, at the labeling of discharge summaries, semantic labels are also extracted from text, such as whether a given disease is present, absent, questionable in a patient, or is unmentioned in the document. The authors...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the American Medical Informatics Association|
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