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

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) mHealth for Patient Education (292) Web-based and Mobile Health Interventions (4018) mHealth for Wellness, Behavior Change and Prevention (3315) Nephrology/Renal Disorders (99)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45531, first published .
Improving Kidney Outcomes in Patients With Nondiabetic Chronic Kidney Disease Through an Artificial Intelligence–Based Health Coaching Mobile App: Retrospective Cohort Study

Improving Kidney Outcomes in Patients With Nondiabetic Chronic Kidney Disease Through an Artificial Intelligence–Based Health Coaching Mobile App: Retrospective Cohort Study

Improving Kidney Outcomes in Patients With Nondiabetic Chronic Kidney Disease Through an Artificial Intelligence–Based Health Coaching Mobile App: Retrospective Cohort Study

Authors of this article:

Wei Liu1, 2 Author Orcid Image ;   Xiaojuan Yu3, 4, 5, 6 Author Orcid Image ;   Jiangyuan Wang7 Author Orcid Image ;   Tianmeng Zhou7 Author Orcid Image ;   Ting Yu2, 8 Author Orcid Image ;   Xuyong Chen7 Author Orcid Image ;   Shasha Xie7 Author Orcid Image ;   Fuman Han7 Author Orcid Image ;   Zi Wang3, 4, 5, 6 Author Orcid Image
Article Authors Cited by (12) Tweetations (5) Metrics

Journals

  1. Soeno S, Liu K, Watanabe S, Sonoo T, Goto T, Shaikh A. Development of novel optical character recognition system to reduce recording time for vital signs and prescriptions: A simulation-based study. PLOS ONE 2024;19(1):e0296319 View
  2. Curtis F, Burton J, Butt A, Dhaliwal H, Graham-Brown M, Lightfoot C, Rawat R, Smith A, Wilkinson T, March D, Wu H. Lifestyle interventions delivered by eHealth in chronic kidney disease: A scoping review. PLOS ONE 2024;19(1):e0297107 View
  3. Dong L, Tan L. Bibliometric and visual analyses of advancements in chronic kidney disease management. Medicine 2024;103(26):e38576 View
  4. Ma J, Wang J, Ying J, Xie S, Su Q, Zhou T, Han F, Xu J, Zhu S, Yuan C, Huang Z, Xu J, Chen X, Bian X. Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Nondialysis-Dependent Chronic Kidney Disease: Retrospective Cohort Study. Journal of Medical Internet Research 2024;26:e54206 View
  5. Hwang M, Zheng Y, Cho Y, Jiang Y. AI Applications for Chronic Condition Self-Management: Scoping Review. Journal of Medical Internet Research 2025;27:e59632 View
  6. Gamal S, Elseasi A, Sabry N, Farid S. Impact of pharmacist led mobile application on medication adherence and efficacy in chronic kidney disease. npj Digital Medicine 2025;8(1) View
  7. Xu J, Guo S, Yu X, Ji X. Willingness and influencing factors of adults receiving Hemodialysis to use mobile healthcare apps: a cross-sectional study. BMC Nephrology 2025;26(1) View
  8. Zeng Y, Yin Y, Deng J, Chen D, Deng L, Wang D, Huang Y, Peng J, Ye Z. Effectiveness of a smart management system in improving adherence and clinical outcomes of patients receiving peritoneal dialysis: a retrospective cohort analysis. BMC Nursing 2025;24(1) View
  9. Nada A, Ahmed Y, Hu J, Weidemann D, Gorman G, Lecea E, Sandokji I, Cha S, Shin S, Bani-Hani S, Mannemuddhu S, Ruebner R, Kakajiwala A, Raina R, George R, Elchaki R, Moritz M. AI-powered insights in pediatric nephrology: current applications and future opportunities. Pediatric Nephrology 2025 View
  10. Yuan S, Guo L, Xu F. Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment. International Urology and Nephrology 2025 View
  11. Ma B, Wang H, Jia Y, Cai Y, Ren X, Hou Y, Zhang M, Chen O. Systematic Review and Network Meta‐Analysis of the Comparative Effectiveness of Self‐Management Support Strategies for Patients With Chronic Kidney Disease. Worldviews on Evidence-Based Nursing 2025;22(6) View

Books/Policy Documents

  1. Chai C, Lau B, Tee M. Innovations in Knowledge Mining: Sustainability for Societal and Industrial Impact. View