Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

Journal: Nutrition, metabolism, and cardiovascular diseases : NMCD
Published Date: Mar 4, 2024

Abstract

BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihypertensive medications.

Authors

  • Jiayi Yi
    National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, China.
  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • Jiali Song
    Department of Biostatistics Beijing, Peking University School of Public Health, No. 38 Xueyuan Road, Haidian District, Beijing, 100000, China.
  • Yanchen Liu
  • Jiamin Liu
  • Haibo Zhang
    Department of Radiology, the Third People's Hospital of Zhongshan, Zhongshan, Guangdong 528451, China.
  • Jiapeng Lu
    National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, China.
  • Xin Zheng
    Department of Clinical Laboratory, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: dearjanna@126.com.

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