LesionMap: A Method and Tool for the Semantic Annotation of Dermatological Lesions for Documentation and Machine Learning
Diagnosis and follow up of patients in dermatology rely on visual cues. Documentation of skin lesions in dermatology is time consuming and inaccurate. Digital photography is resource intensive, difficult to standardize, and has privacy concerns. We propose a simple method LesionMap and an electronic health software tool LesionMapper for semantically annotating dermatological lesions on a body wireframe. We discuss how the type, distribution, and progression of lesions can be represented in a standardized way. The tool is an open source JavaScript package that can be integrated into web based electronic medical records. We believe that LesionMapper will facilitate documentation in dermatology that can be used for machine learning in a privacy preserving manner. (JMIR Dermatol 2020;3(1):e18149) doi: 10.2196/18149