Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Chronic Obstructive Pulmonary Disease-V: Management01:29

Chronic Obstructive Pulmonary Disease-V: Management

3.1K
Managing Chronic Obstructive Pulmonary Disease (COPD) involves a multifaceted approach to reduce symptoms, prevent exacerbations, improve overall health status, and slow disease progression. Key strategies include lifestyle modifications, pharmacotherapy, supportive therapies, and, in some cases, surgery. Here is an overview of the primary COPD management strategies:
Smoking Cessation
3.1K
Chronic Obstructive Pulmonary Disease-V: Nursing Management01:30

Chronic Obstructive Pulmonary Disease-V: Nursing Management

5.1K
Nursing management of Chronic Obstructive Pulmonary Disease (COPD) is crucial for providing thorough care and support to patients. Nurses play an integral role in this process through detailed assessment, careful planning, targeted interventions, and ongoing evaluation. Here's an overview of the critical steps in nursing management for COPD.
Assessment
5.1K
Chronic Kidney Disease IV: Nursing Management01:18

Chronic Kidney Disease IV: Nursing Management

368
Nursing management is essential for preventing complications, maintaining stability, and improving patients' quality of life in chronic kidney disease (CKD). By using a structured approach, nurses help slow CKD progression and support effective patient care​.1. Comprehensive patient assessmentEffective management begins with nurses reviewing the patient’s medical history, and identifying key risk factors like diabetes, hypertension, and nephrotoxic drug use. Nurses assess signs of...
368
Levels of Health Promotion and Illness Prevention01:26

Levels of Health Promotion and Illness Prevention

14.5K
Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
In primary prevention, actions taken before disease onset prevent the disease from...
14.5K
Models of Health Promotion and Illness Prevention I01:25

Models of Health Promotion and Illness Prevention I

2.8K
A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
2.8K
Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

2.1K
The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results...
2.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Uncovering Novel Atrial Fibrillation Genetics Through Pleiotropic Overlap with Life's Essential 8.

Biomedicines·2026
Same author

Neurobehavioural genes exert indirect genetic effects on blood lipid profiles through behavioural traits.

Communications biology·2026
Same author

Inverted U-Shaped Association Between Serum Uric Acid and Handgrip Strength in Chinese Community-Dwelling Adults: A Repeated-Measures Cohort Study.

Biomedicines·2026
Same author

Moderate-to-vigorous physical activity promotion and grip strength improvement in Chinese community-dwelling older adults: a 12-month pragmatic intervention study.

Age and ageing·2026
Same author

Diet-Gene Interaction Between Fruit Intake and <i>CMIP</i> rs2925979 Polymorphism in Relation to Type 2 Diabetes: A Family-Based Study in Northern China.

Nutrients·2025
Same author

Parental Transmission of Type 2 Diabetes Risk in Offspring: A Prospective Family-Based Cohort Study in Northern China.

Nutrients·2025

Related Experiment Video

Updated: Jan 29, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

882

Digital-Intelligent Precision Health Management: An Integrative Framework for Chronic Disease Prevention and Control.

Yujia Ma1,2, Dafang Chen3,4, Jin Xie1,2

  • 1Department of Non-communicable Chronic Disease Control and Prevention, Beijing Center for Disease Prevention and Control, Beijing 100013, China.

Biomedicines
|January 28, 2026
PubMed
Summary

Digital-intelligent precision health management offers a proactive approach to non-communicable diseases (NCDs). This framework integrates continuous sensing, AI-driven diagnostics, and personalized interventions for better long-term health outcomes.

Keywords:
artificial intelligencedigital healthnon-communicable diseasesprecision medicine

More Related Videos

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.4K
Assessment of Vascular Function in Patients With Chronic Kidney Disease
08:50

Assessment of Vascular Function in Patients With Chronic Kidney Disease

Published on: June 16, 2014

16.7K

Related Experiment Videos

Last Updated: Jan 29, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

882
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.4K
Assessment of Vascular Function in Patients With Chronic Kidney Disease
08:50

Assessment of Vascular Function in Patients With Chronic Kidney Disease

Published on: June 16, 2014

16.7K

Area of Science:

  • Digital health
  • Precision medicine
  • Artificial intelligence in healthcare

Background:

  • Non-communicable diseases (NCDs) present a significant global health challenge, with current hospital-centered, reactive care models being inadequate for their complex nature.
  • Existing healthcare systems struggle to manage the long-term, multifactorial aspects of NCDs effectively.
  • Advances in digital technologies, AI, and precision medicine necessitate a new, integrated approach to health management.

Purpose of the Study:

  • To introduce and define the framework of digital-intelligent precision health management.
  • To explore the three interdependent dimensions of this integrated health management approach.
  • To synthesize recent literature, examine challenges, and outline future directions for this framework.

Main Methods:

  • Multidimensional health-related phenotyping using continuous digital sensing, wearables, ambient devices, and multi-omics profiling.
  • Intelligent risk warning and early diagnosis leveraging machine learning for dynamic risk prediction and early pathological deviation detection.
  • Health management through intelligent decision-making, incorporating digital twins and AI health agents for personalized interventions and closed-loop management.

Main Results:

  • The framework enables comprehensive, longitudinal characterization of individual health states in real-world settings.
  • Advanced machine learning algorithms facilitate dynamic risk prediction and refined disease stratification.
  • Integration of digital twins and AI agents supports personalized intervention planning, virtual simulation, and adaptive optimization.

Conclusions:

  • Digital-intelligent precision health management represents a paradigm shift from passive care to proactive, anticipatory, and individual-centered health management.
  • This integrated framework addresses the limitations of traditional NCD care by leveraging technology and AI.
  • Further research and ethical considerations are needed to embed this framework into broader healthcare and population health systems.