511 citations · 1k across the 5 of their papers we have counts for
5 papers
Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set
Roxana Daneshjou, Kailas Vodrahalli, Roberto A Novoa +16
Access to dermatological care is a major issue, with an estimated 3 billion people lacking access to care globally. Artificial intelligence (AI) may aid in triaging skin diseases.…
Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang +14
More than 3 billion people lack access to care for skin disease. AI diagnostic tools may aid in early skin cancer detection; however most models have not been assessed on images of…
Towards Realization of Augmented Intelligence in Dermatology: Advances and Future Directions
Roxana Daneshjou, Carrie Kovarik, Justin M Ko
Artificial intelligence (AI) algorithms using deep learning have advanced the classification of skin disease images; however these algorithms have been mostly applied "in silico" a…
TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos
Kailas Vodrahalli, Roxana Daneshjou, Roberto A Novoa +3
Telehealth is an increasingly critical component of the health care ecosystem, especially due to the COVID-19 pandemic. Rapid adoption of telehealth has exposed limitations in the…
Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning
Yunzhu Li, Andre Esteva, Brett Kuprel +3
Dense object detection and temporal tracking are needed across applications domains ranging from people-tracking to analysis of satellite imagery over time. The detection and track…