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This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3756) mHealth in a Clinical Setting (807) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1858) Formative Evaluation of Digital Health Interventions (3599) Nursing and Care for Patients with Infectious or Chronic Conditions (39) Chronic Conditions (503) Nurses Supporting Self-Management of Chronic Diseases (24) Nephrology/Renal Disorders (118)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54206, first published .
Phone displaying lab records app showing urine protein quantification graph and lab tests.

Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Nondialysis-Dependent Chronic Kidney Disease: Retrospective Cohort Study

Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Nondialysis-Dependent Chronic Kidney Disease: Retrospective Cohort Study

Authors of this article:

Jianwei Ma1, 2 Author Orcid Image ;   Jiangyuan Wang3 Author Orcid Image ;   Jiapei Ying1 Author Orcid Image ;   Shasha Xie3 Author Orcid Image ;   Qin Su1 Author Orcid Image ;   Tianmeng Zhou3 Author Orcid Image ;   Fuman Han3 Author Orcid Image ;   Jiayan Xu4 Author Orcid Image ;   Siyi Zhu5 Author Orcid Image ;   Chenyi Yuan1 Author Orcid Image ;   Ziyuan Huang1 Author Orcid Image ;   Jingfang Xu1 Author Orcid Image ;   Xuyong Chen3 Author Orcid Image ;   Xueyan Bian1 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Bhatt P, Chhillar M, Kumar A, Kukkar D, Kukkar M. Recent advancements in patented technologies for the diagnosis and treatment of chronic kidney disease. International Urology and Nephrology 2025;57(9):3045 View
  2. VO M, NGUYEN H, NGUYEN D. THE ROLE OF DIGITAL COMPETENCY IN AI-DRIVEN HEALTH MONITORING FOR THE ELDERLY: A QUANTITATIVE STUDY ON SYSTEM EFFECTIVENESS. Journal Health and Technology - JHT 2025;6(1):e4164 View
  3. Cervantes C, O’Hara D, Alvarez-Elias A, Chandra Y, Kollar M, Yi T, Hussein R, Shankar M, Meena P, Ma B, Okwuonu C, Jha V, Cervantes C, O'Hara D. Expanding Kidney Care: How Nonphysician Health Workers Can Address the Global CKD Crisis. Kidney International Reports 2026;11(3):103625 View
  4. Thongprayoon C, Pesce F, Cheungpasitporn W. Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence—A Roadmap for Workflow-Integrated Care. Journal of Clinical Medicine 2026;15(7):2576 View
  5. Patel D, Han D, Segal J. Measurement Properties of an Electronic Patient-Reported Outcome Measure for Patients with Non–Dialysis-Dependent CKD. Kidney360 2026;7(4):823 View
  6. Olejnik A, Możdżan M, Biskup L, Zheng E, Huszcza B, Gronek K, Kaczmarek J, Grandos J, Gajewski D, Głowacka Z, Kościołek K. THE EVOLUTION OF AI MEDICAL CONSULTANTS AND THEIR IMPACT ON PATIENT EDUCATION: A LITERATURE REVIEW. International Journal of Innovative Technologies in Social Science 2026;4(1(49)) View
  7. Tang D, Liang M, Wang W, Liang Y, Khatra H. Self‐Management Intentions and Behaviors Among CKD Patients at Predialysis and Dialysis Stages: A Cross‐Sectional Study Based on Protection Motivation Theory. Nursing Research and Practice 2026;2026(1) View

Books/Policy Documents

  1. Pedraza-Choque P, Cabanillas-Carbonell M. Advances in Digital Health and Medical Bioengineering II. View