Comorbidity and multimorbidity prediction of major chronic diseases using machine learning and network analytics

作者：

Highlights：

• Develop models to predict comorbidity and multimorbidity of major chronic diseases.

• Apply network analytics to extract features from patient networks.

• XGBoost showed the best accuracy for chronic disease comorbidity and multimorbidity.

• Demonstrate an important use of administrative claim data.

摘要

•Develop models to predict comorbidity and multimorbidity of major chronic diseases.•Apply network analytics to extract features from patient networks.•XGBoost showed the best accuracy for chronic disease comorbidity and multimorbidity.•Demonstrate an important use of administrative claim data.

论文关键词：Disease comorbidity,Disease multimorbidity,Machine learning,Patient-disease network

论文评审过程：Received 1 February 2022, Revised 31 May 2022, Accepted 2 June 2022, Available online 6 June 2022, Version of Record 10 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117761