WIP: Medical Incident Prediction Through Analysis of Electronic Medical Records Using Machine Lerning: Fall Prediction
Authors: Atsushi Yanagisawa, Chintaka Premachandra, Hiruharu Kawanaka, Atsushi Inoue, Takeo Hata, Eiichiro Ueda
Abstract: This paper reports our preliminary work on medical incident prediction in general, and fall risk prediction in specific, using machine learning. Data for the machine learning are generated only from the particular subset of the electronic medical records (EMR) at Osaka Medical and Pharmaceutical University Hospital. As a result of conducting three experiments such as (1) machine learning algorithm comparison, (2) handling imbalance, and (3) investigation of explanatory variable contribution to the fall incident prediction, we find the investigation of explanatory variables the most effective.
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