Access to a dermatologist or any other specialist in a rural town or small city can be a challenge. Primary care doctors sometimes lack the resources and training to diagnose skin lesions and certain rare conditions. In order to avoid making wrong decisions, primary care doctors are turning to VisualDx, a deep learning symptom-identifying app that can eliminate the knowledge gap for non-specialists.
Started by Art Papier, MD, an associate professor in dermatology at the University of Rochester Medical School, VisualDx has archived 20 years of diagnostic images and is used in hundreds of hospitals and clinics throughout the country. Papier’s mission for the app is to eliminate misdiagnoses, and claims to increase diagnostic accuracy by 120 percent.
VisualDx recently introduced Derm Expert, a new feature specifically geared toward helping physicians correctly identify skin lesions that they otherwise wouldn’t know how to assess. The clinician snaps a photo of the area and gives the app a brief synopsis of the patient’s medical history, including prescriptions and recent travels. VisualDx then generates a list of possible diagnoses pointing to potential causing factors.
VisualDx + Derm Expert operates with Core ML, a trained machine learning model that makes sure all patient data is HIPAA-compliant by locally storing confidential files. The app is available in the Apple App Store, and offers various subscription plans. Papier plans to release a consumer-directed app for patients who are curious about evaluating possible skin lesions.