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AutoScribe: Extracting Clinically Pertinent Information from Patient-Clinician Dialogues
Faiza Khan Khattak1,2, Serena Jeblee1,2, Noah Crampton3
1Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
Abstract:
We present AutoScribe, a system for automatically extracting pertinent medical information from dialogues between clinicians and patients. AutoScribe parses the dialogue and extracts entities such as medications and symptoms, using context to predict which entities are relevant, and automatically generates a patient note and primary diagnosis.
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