The Classification of Medical Events Using Latent Semantic Analysis

Abstract

Clinical information is dominated by natural language representation of data and knowledge. To bring quantitative methods to bear in the empiric analysis of clinical episodes, they must be classified into reasonably homogenous categories that sustain inference and generalization. A tangible, if trivial, example of a classification requirement is the retrieval of patient cases relevant to the testing of a clinical hypothesis, so that they can be further scrutinized. Reliance on text word retrieval alone, drawn from natural language summaries, is fraught with contextual ambiguity and defeated by an expressively rich sub-language.