Unified Approaches For Skin Cancer Detection: A Systematic Aspect Of Review Of Support Vector Machines To Resnet-50, And Deep Learning Models

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Systematic review evaluates skin cancer detection using AI, suggesting deep learning methods improve accuracy and sensitivity.

Deep learning models, particularly resnet-50, outperform traditional methods, achieving over 92% accuracy.
Sensitivity rates for resnet-50 reach up to 94.3%, with AUC values above 0.96 in large datasets.
Traditional support vector machines maintain high discriminative power in low-resource datasets, aiding diagnostic efficiency.
Challenges remain in model transparency and the need for evidence in training on diverse skin types.

Ahmad et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark