August 26, 2025EClinicalMedicine7 citationsOpen Access

Machine learning-based phenotyping and assessment of treatment responses in heart failure with preserved ejection fraction

RLRui LiPeking University YLYijun LiuChinese Academy of Sciences ZZZhen ZhaoChinese Academy of Sciences

Structured PICO

Population

Patients with heart failure with preserved ejection fraction

Intervention

Machine learning-based phenotyping and assessment of treatment responses

Abstract

This study was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0539000), National Natural Science Foundation of China (82300291), Beijing Nova Program (20230484275), University of Michigan Medical School (UMMS) and Peking University Health Science Center (PKUHSC) Joint Institute for Translational and Clinical Research (BMU2023JI004), Clinical Cohort Construction Program of Peking University Third Hospital (BYSYDL2023009), CAMS Innovation Fund for Medical Sciences (2021-I2M-5-003), Peking University Shi-Ji Jin-Yuan Medical Foundation (48014Y0243), and Beijing Excellent Clinical Research Program (BRWEP2024W014090203).

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