Advances in Image-Based Diagnosis of Diabetic Foot Ulcers Using Deep Learning and Machine Learning: A Systematic Review.

ABSTRACT: Background/Objectives: This review systematically assesses machine learning (ML) and deep learning (DL) applications using images to diagnose diabetic foot ulcers (DFUs), focusing on detection, segmentation, and classification. The study explores trends, challenges, and quality measurements of the reviewed research. Methods: A comprehensive search was conducted in October 2025 across 14 databases, covering studies published between 2010 and 2025. Studies employing ML/DL for DFU diagnosis with accurate measurements were included, while those without image-based methods, AI techniques, or relevant outcomes were excluded. Out of 4653 articles initially identified, 1016 underwent detailed review, and 102 met the inclusion criteria. Results: The analysis revealed that ML/DL

SUBMITTER: Alhasson HF 

PROVIDER: S-EPMC12730623 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature