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Improving Diabetic Foot Care With Infrared Thermography and Artificial Intelligence: A Review
Pedro Teixeira1, Vítor Filipe1,2, Ana Teixeira1,3
1University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.
Journal of Diabetes Science and Technology
|April 4, 2026
Summary
Infrared thermography (IRT) combined with artificial intelligence (AI) shows promise for identifying diabetic foot complications. This AI-driven approach can help predict ulceration risk and improve patient management.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Diabetology
Background:
- Diabetic foot complications, including ulcers and amputation, are a significant concern.
- Plantar region temperature increases correlate with higher ulceration risk.
- Infrared thermography (IRT) and AI-based systems offer advanced tools for early detection and management.
Purpose of the Study:
- To analyze the current research on using IRT and AI for diabetic foot complication identification and risk prediction.
- To evaluate the effectiveness of these combined technologies in clinical practice.
Main Methods:
- Systematic review and analysis of 37 research papers.
- Focus on studies employing thermography and artificial intelligence for diabetic foot assessment.
Main Results:
- IRT combined with AI demonstrates significant potential for identifying and predicting diabetic foot complications.
- These technologies can enhance diagnostic accuracy and support clinical decision-making.
Conclusions:
- The synergy of IRT and AI presents a powerful approach for diabetic foot assessment.
- Current research is largely limited to classifying foot thermograms from curated datasets.
- Further research is needed in segmentation methods and deep learning applications, particularly with larger, diverse datasets.
