Artificial intelligence-based automated grading and severity prediction of radiation dermatitis: a review.

IMPORTANCE

Radiation dermatitis (RD) is a common complication of radiotherapy, affecting up to 90% of patients. AI-based automated assessment may improve objective grading and predictive accuracy.

OBJECTIVE

To review AI applications in RD detection, grading, and severity prediction. EVIDENCE REVIEW: This review summarizes the promising application of deep learning for automated RD grading and identifies a distinct lack of research into AI models for predicting its progression. FINDINGS: AI shows promise in reducing interobserver variability and enabling early intervention. Challenges include dataset limitations and lack of cross-center validation.

CONCLUSIONS

AI-based tools have potential for personalized RD management, but further multicenter validation is needed. CLINICAL TRIAL REGISTRATION: Clinical Trial registration: ChiCTR2400082684