A deep learning model for histopathological diagnosis of actinic keratosis: a diagnostic case control accuracy study

Key Points

• The study aims to evaluate the accuracy of deep learning models in diagnosing actinic keratosis using histopathological images.
• Developed a deep learning model (DLM) for diagnosis.
• Conducted a diagnostic case control study.
• Analyzed routine dermatopathology samples for accuracy.
• DLMs demonstrated reliable detection of actinic keratosis.
• Improvements in diagnostic accuracy were noted with advanced technology.

Abstract