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

Patient and Public Involvement in Research (68) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (2300) Home Care (235) Design and Usability of Medical Devices (211) mHealth for Telemedicine and Homecare (838) Design and Usability of Consumer Health Tech and Home Monitoring Devices (438) Artificial Intelligence (4533)

Published on in Vol 17 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69470, first published .
Hand holding iPhone showing wound care app with wound progress

Empowering Patients and Caregivers to Use Artificial Intelligence and Computer Vision for Wound Monitoring: Nonrandomized, Single-Arm Feasibility Study

Empowering Patients and Caregivers to Use Artificial Intelligence and Computer Vision for Wound Monitoring: Nonrandomized, Single-Arm Feasibility Study

Authors of this article:

Rose Raizman1, 2 Author Orcid Image ;   José Luis Ramírez-GarciaLuna3 Author Orcid Image ;   Tanmoy Newaz4 Author Orcid Image ;   Sheila C Wang5, 6, 7 Author Orcid Image ;   Gregory K Berry3 Author Orcid Image ;   Ling Yuan Kong8, 9 Author Orcid Image ;   Heba Tallah Mohammed6 Author Orcid Image ;   Robert D J Fraser6, 10 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

Journals

  1. Grunhut J, Nagarsheth K. Artificial Intelligence for Postoperative Wound Monitoring: An Integrative Review of Digital Innovation and Clinical Feasibility. The American Surgeon™ 2026;92(3):929 View
  2. Sen C, DeMazumder D. Getting Started on Artificial Intelligence in Health Care and Clinical Research: Includes Rigor Checklist for Authors and Reviewers. Advances in Wound Care 2025 View
  3. Wei Y, Liu X, Pei J, Zhang H, Han L. Artificial Intelligence in Pressure Injury Diagnosis: A Critical Appraisal for Clinical Practice. Advances in Wound Care 2025 View
  4. Abodunrin O, Atoyebi E, Bricha M, Mabrouk K. Innovative wound nanofiber mats: revolutionizing wound care through quality by design and artificial intelligence. Biomedical Materials Science 2026;1(1) View
  5. Yu C, Murray M, Wei R, Cope V. Digital platforms and shared decision-making tools for home wound care: An integrative review. International Journal of Nursing Studies 2026;182:105609 View
  6. Yu Z, Jiang L, Zhang H, Chen H, Li J. A clinically aligned multimodal workflow framework for chronic wound assessment: An evidence-informed conceptual modeling study. DIGITAL HEALTH 2026;12 View
  7. Katorkin S. Potential of artificial intelligence methods in diseases of the venous system of the lower extremities. Ambulatornaya khirurgiya = Ambulatory Surgery (Russia) 2026;23(1):15 View