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.
翻译:本文报告我们关于一般医疗事故预测的初步工作,以及利用机器学习的具体风险预测;机器学习数据仅来自大阪医药大学医院电子医疗记录的特定子集;通过进行三项实验,例如:(1)机器学习算法比较,(2)处理不平衡,(3)调查对秋季事故预测的解释性变量贡献,我们发现对解释性变量的调查最为有效。