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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

The overall model was not statistically significant (F-statistic=1.010; P=.46), indicating that the predictors collectively explained only a small proportion of the variance in the temperature delta. The R2 (uncentered) value was 0.224, and the adjusted R2 (uncentered) was 0.002, suggesting a weak fit of the model to the data. However, diabetes status remained a statistically significant predictor of temperature delta (β=5.544; P=.02; 95% CI of 1.064-10.024).

Meshari F Alwashmi, Mustafa Alghali, AlAnoud AlMogbel, Abdullah Abdulaziz Alwabel, Abdulaziz S Alhomod, Ibrahim Almaghlouth, Mohamad-Hani Temsah, Amr Jamal

JMIR Diabetes 2025;10:e65209