Articles | Volume 11, issue 5
https://doi.org/10.5194/jbji-11-623-2026
https://doi.org/10.5194/jbji-11-623-2026
Review
 | 
13 Oct 2026
Review |  | 13 Oct 2026

Machine learning in diabetic-foot osteomyelitis: current applications, challenges, and future directions

Farzad Pourghazi, Seyed Mohammad Amin Alavi, Francesco Petri, Takahiro Matsuo, Sergio Alvarez Mulett, Fabio Borgonovo, Andrea Gori, Michael E. Torchia, Aaron J. Tande, and Elie F. Berbari
Metrics will be available soon.
Latest update: 13 Oct 2026
Download
Short summary
Diabetic-foot bone infection is difficult to diagnose, and machine learning may help clinicians use clinical information and medical images. We reviewed studies that developed or evaluated these models for diabetic-foot osteomyelitis. Most focused on diagnosis using either clinical and laboratory information or imaging. No study combined these sources, and testing in new groups was uncommon. Future research should combine clinical information with imaging and test models in other groups.
Share