Development of an Interpretable Machine Learning Model for Predicting Individual Response to Antihypertensive Treatments

被引：0
|
作者：
Yi, Jiayi
Wang, Lili
Liu, Yanchen
Liu, Jiamin
Zhang, Haibo
Zheng, Xin
机构：
来源：
CIRCULATION | 2023年 / 148卷
关键词：
Hypertension; Machine Learning; Prediction model; Blood pressure determination;
D O I：
10.1161/circ.148.suppl_1.15033
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
A15033
引用
收藏
页数：2
相关论文
共 50 条
  • [21] MrIML: Multi-response interpretable machine learning to model genomic landscapes
    Fountain-Jones, Nicholas M.
    Kozakiewicz, Christopher P.
    Forester, Brenna R.
    Landguth, Erin L.
    Carver, Scott
    Charleston, Michael
    Gagne, Roderick B.
    Greenwell, Brandon
    Kraberger, Simona
    Trumbo, Daryl R.
    Mayer, Michael
    Clark, Nicholas J.
    Machado, Gustavo
    MOLECULAR ECOLOGY RESOURCES, 2021, 21 (08) : 2766 - 2781
  • [22] Interpretable machine learning for predicting the fate and transport of pentachlorophenol in groundwater
    Rad, Mehran
    Abtahi, Azra
    Berndtsson, Ronny
    Mcknight, Ursula S.
    Aminifar, Amir
    ENVIRONMENTAL POLLUTION, 2024, 345
  • [23] Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods
    Yuran Sun
    Shih-Kai Huang
    Xilei Zhao
    International Journal of Disaster Risk Science, 2024, 15 : 134 - 148
  • [24] Predicting the evolution of scientific communities by interpretable machine learning approaches
    Tian, Yunpei
    Li, Gang
    Mao, Jin
    JOURNAL OF INFORMETRICS, 2023, 17 (02)
  • [25] Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods
    Yuran Sun
    Shih-Kai Huang
    Xilei Zhao
    InternationalJournalofDisasterRiskScience, 2024, 15 (01) : 134 - 148
  • [26] Predicting and understanding residential water use with interpretable machine learning
    Rachunok, Benjamin
    Verma, Aniket
    Fletcher, Sarah
    ENVIRONMENTAL RESEARCH LETTERS, 2024, 19 (01)
  • [27] Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods
    Sun, Yuran
    Huang, Shih-Kai
    Zhao, Xilei
    INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE, 2024, 15 (01) : 134 - 148
  • [28] Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning
    Wan, Qingyun
    Liu, Kai
    Bo, Yuyang
    Yuan, Xiya
    Li, Mufeng
    Wang, Xiaoqiu
    Chen, Chuang
    Liu, Lanying
    Wu, Wenzhong
    IEEE ACCESS, 2025, 13 : 45964 - 45984
  • [29] Interpretable machine learning in predicting drug-induced liver injury among tuberculosis patients: model development and validation study
    Xiao, Yue
    Chen, Yanfei
    Huang, Ruijian
    Jiang, Feng
    Zhou, Jifang
    Yang, Tianchi
    BMC MEDICAL RESEARCH METHODOLOGY, 2024, 24 (01)
  • [30] An Interpretable Machine Learning Model for Predicting Long-Term Clinical Outcomes in Recurrent Pericarditis
    Yesilyaprak, Abdullah
    Kumar, Ashwin
    Furqan, Muhammad M.
    Verma, Beni R.
    Agrawal, Ankit
    Syed, Alveena
    Akyuz, Kevser
    Wang, Tom Kai Ming K.
    Cremer, Paul C.
    Klein, Allan L.
    CIRCULATION, 2022, 146
12345