TY - JOUR
AU - Y. Ma
AU - D. Chen
AU - J. Xie
A1 - 
AB - Non-communicable diseases (NCDs) impose an overwhelming burden on global health systems. Prevailing healthcare for NCDs remains largely hospital-centered, episodic, and reactive, rendering them poorly suited to address the long-term, heterogeneous, and multifactorial nature of NCDs. Rapid advances in digital technologies, artificial intelligence (AI), and precision medicine have catalyzed the development of an integrative framework for digital-intelligent precision health management, characterized by the functional integration of data, models, and decision support. It is best understood as an integrated health management framework operating across three interdependent dimensions. First, it is grounded in multidimensional health-related phenotyping, enabled by continuous digital sensing, wearable and ambient devices, and multi-omics profiling, which together allow for comprehensive, longitudinal characterization of individual health states in real-world settings. Second, it leverages intelligent risk warning and early diagnosis, whereby multimodal data are fused using advanced machine learning algorithms to generate dynamic risk prediction, detect early pathological deviations, and refine disease stratification beyond conventional static models. Third, it culminates in health management under intelligent decision-making, integrating digital twins and AI health agents to support personalized intervention planning, virtual simulation, adaptive optimization, and closed-loop management across the disease continuum. Framed in this way, digital-intelligent precision health management enables a fundamental shift from passive care towards proactive, anticipatory, and individual-centered health management. This Perspectives article synthesizes recent literature from the past three years, critically examines translational and ethical challenges, and outlines future directions for embedding this framework within population health and healthcare systems.
AD - Department of Non-communicable Chronic Disease Control and Prevention, Beijing Center for Disease Prevention and Control, Beijing 100013, China.; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China.; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
AN - 41595757
BT - Biomedicines
C5 - HIT & Telehealth
CP - 1
DA - Jan 20
DO - 10.3390/biomedicines14010223
DP - NLM
ET - 20260120
IS - 1
JF - Biomedicines
LA - eng
N2 - Non-communicable diseases (NCDs) impose an overwhelming burden on global health systems. Prevailing healthcare for NCDs remains largely hospital-centered, episodic, and reactive, rendering them poorly suited to address the long-term, heterogeneous, and multifactorial nature of NCDs. Rapid advances in digital technologies, artificial intelligence (AI), and precision medicine have catalyzed the development of an integrative framework for digital-intelligent precision health management, characterized by the functional integration of data, models, and decision support. It is best understood as an integrated health management framework operating across three interdependent dimensions. First, it is grounded in multidimensional health-related phenotyping, enabled by continuous digital sensing, wearable and ambient devices, and multi-omics profiling, which together allow for comprehensive, longitudinal characterization of individual health states in real-world settings. Second, it leverages intelligent risk warning and early diagnosis, whereby multimodal data are fused using advanced machine learning algorithms to generate dynamic risk prediction, detect early pathological deviations, and refine disease stratification beyond conventional static models. Third, it culminates in health management under intelligent decision-making, integrating digital twins and AI health agents to support personalized intervention planning, virtual simulation, adaptive optimization, and closed-loop management across the disease continuum. Framed in this way, digital-intelligent precision health management enables a fundamental shift from passive care towards proactive, anticipatory, and individual-centered health management. This Perspectives article synthesizes recent literature from the past three years, critically examines translational and ethical challenges, and outlines future directions for embedding this framework within population health and healthcare systems.
PY - 2026
SN - 2227-9059 (Print); 2227-9059
ST - Digital-Intelligent Precision Health Management: An Integrative Framework for Chronic Disease Prevention and Control
T1 - Digital-Intelligent Precision Health Management: An Integrative Framework for Chronic Disease Prevention and Control
T2 - Biomedicines
TI - Digital-Intelligent Precision Health Management: An Integrative Framework for Chronic Disease Prevention and Control
U1 - HIT & Telehealth
U3 - 10.3390/biomedicines14010223
VL - 14
VO - 2227-9059 (Print); 2227-9059
Y1 - 2026
ER -