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The rapidly expanding corpus of medical research literature presents majorchallenges in the understanding of previous work, the extraction of maximuminformation from collected data, and the identification of promising researchdirections. We present a case for the use of advanced machine learningtechniques as an aide in this task and introduce a novel methodology that isshown to be capable of extracting meaningful information from largelongitudinal corpora, and of tracking complex temporal changes within it.

Identification of promising research directions using machine learning aided medical literature analysis