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

Artificial Intelligence (2333) Chronic Foot Ulcer and Wounds (24) Pressure Ulcers and Decubitus Wounds (30) Machine Learning (2223) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (103)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69408, first published .
Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review

Authors of this article:

Manuel Alberto Silva1, 2 Author Orcid Image ;   Emma J Hamilton3, 4 Author Orcid Image ;   David A Russell5, 6 Author Orcid Image ;   Fran Game7 Author Orcid Image ;   Sheila C Wang8, 9 Author Orcid Image ;   Sofia Baptista10, 11, 12 Author Orcid Image ;   Matilde Monteiro-Soares11, 13, 14 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Journals

  1. Gao L, Liu Z, Han S, Wang J. A Machine-Learning-Based Clinical Decision Model for Predicting Amputation Risk in Patients with Diabetic Foot Ulcers: Diagnostic Performance and Practical Implications. Diagnostics 2025;15(24):3142 View
  2. Seliverstov P, Zakrevsky V, Ivaniuk A, Kerimova А, Maltsev S, Tokarev K. A personalized approach to the treatment and prevention of diabetic foot: molecular mechanisms and the role of taxifolin. Molekulyarnaya Meditsina (Molecular medicine) 2025:30 View
  3. Arciola C, Panichi V, Bua G, Costantini S, Bottau G, Ravaioli S, Capponi E, Campoccia D. Smart Healing for Wound Repair: Emerging Multifunctional Strategies in Personalized Regenerative Medicine and Their Relevance to Orthopedics. Antibiotics 2026;15(1):36 View
  4. Basiri R, Saleh A, Khan S, Popovic M. Temporal machine learning framework for diabetic foot ulcer healing trajectory prediction. BioMedical Engineering OnLine 2026;25(1) View
  5. Menon G, Jose S, Jose S, Thomas J, Jirawattanapanit A. Predicting lower limb amputation risk based on clinical factors and wound characteristics using machine learning. Physica Scripta 2026;101(10):105004 View

Conference Proceedings

  1. Acharya P, Acharya S. 2025 Modern Electronics Devices and Intelligent Communication Systems (MEDCOM). Image-Based Detection and Classification of Skin Ulcers Using Deep Learning View