The Journal of investigative dermatology
Nov 18, 2023
The field of skin cancer detection offers a compelling use case for the application of artificial intelligence (AI) within the realm of image-based diagnostic medicine. Through the analysis of large datasets, AI algorithms have the capacity to classi...
The Journal of investigative dermatology
Feb 17, 2023
Noninvasive quantification of dermal diseases aids efficacy studies and paves the way for broader enrollment in clinical studies across varied demographics. Related to atopic dermatitis, accurate quantification of the onset and resolution of inflamma...
The Journal of investigative dermatology
Oct 30, 2021
Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing who...
The Journal of investigative dermatology
Oct 23, 2021
Ex vivo confocal microscopy (EVCM) generates digitally colored purple-pink images similar to H&E without time-consuming tissue processing. It can be used during Mohs surgery for rapid detection of basal cell carcinoma (BCC); however, reading EVCM ima...
The Journal of investigative dermatology
Jul 13, 2021
Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied ...
The Journal of investigative dermatology
Mar 22, 2021
Artificial intelligence (AI)-based applications have the potential to improve the quality and efficiency of patient care in dermatology. Unique challenges in the development and validation of these technologies may limit their generalizability and re...