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Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study
2017
Machine Learning in Health Care
Clinical diagnostic inferencing is a complex task, which often requires significant medical research and investigation based on an underlying clinical scenario. This paper proposes a novel approach by formulating the task as a reinforcement learning problem such that the system can infer the most probable diagnoses by optimizing clinical concept extraction from a free text case narrative via leveraging relevant external evidence. Such a formulation is deemed to be suitable due to the inherent
dblp:conf/mlhc/LingHDQLLF17
fatcat:oyoqpaatiffmlhmrjjlwbvhev4