Personalized medical reading recommendation: Deep semantic approach

Abstract

Therapists are faced with the overwhelming task of identifying, reading, and incorporating new information from a vast and fast growing volume of publications into their daily clinical decisions. In this paper, we propose a system that will semantically analyze patient records and medical articles, perform medical domain specific inference to extract knowledge profiles, and finally recommend publications that best match with a patient’s health profile. We present specific knowledge extraction and matching details, examples, and results from the mental health domain.