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Published on in Vol 10 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65209, first published .
Woman uses a glucose meter to check blood sugar levels with a diabetes kit.

The Use of AI-Powered Thermography to Detect Early Plantar Thermal Abnormalities in Patients With Diabetes: Cross-Sectional Observational Study

The Use of AI-Powered Thermography to Detect Early Plantar Thermal Abnormalities in Patients With Diabetes: Cross-Sectional Observational Study

Journals

  1. Alwashmi M, alghali M, Abu-Ashour W, Arabe A, Al Soheimi A, Alharbi N, Badahdah H. AI-Powered Thermography for Diabetic Foot Risk Stratification: Multicenter Cross-Sectional Study. JMIR Formative Research 2025;9:e81289 View
  2. Iturriago-Salas L, Mesa-Sarmiento J, Castro-Cabrera P, Álvarez-Meza A, Castellanos-Dominguez G. Artificial Intelligence-Driven Mobile Platform for Thermographic Imaging to Support Maternal Health Care. Computers 2025;14(11):466 View
  3. Shara K, Alghali M, Abu-Ashour W, Almnaizel A, Sunbul T, Baatiah N, Attal K, Al Attallah I, Sawad B, Alwashmi M. Combining thermography and artificial intelligence in comparison with a diabetic foot nurse for diabetic foot ulcer detection: A diagnostic accuracy study. DIGITAL HEALTH 2026;12 View
  4. Chingan-Martino V, Allali M, Henri S, Guène E, Gibert D, Chéret A. Clinical Thermography of the Diabetic Foot Using a Low-Cost Thermal Camera: Processing and Instrumental Framework. Sensors 2026;26(8):2438 View
  5. Chauhan P, Sikka G, Prakash C. k–GCNDFU: An explainable relational manifold learning framework for diabetic foot ulcer classification. Signal, Image and Video Processing 2026;20(5) View
  6. Moj K, Arseniy I, Żak K, Malicki D, Oszkinis G. 3D Measurement of Chronic Wounds in Routine Care: A Review with Practical Guidance for Smartphone Photogrammetry. Annals of Biomedical Engineering 2026 View