3 papers
cs.LG2025
On the Role of Calibration in Benchmarking Algorithmic Fairness for Skin Cancer Detection
Brandon Dominique, Prudence Lam, Nicholas Kurtansky +4
Artificial Intelligence (AI) models have demonstrated expert-level performance in melanoma detection, yet their clinical adoption is hindered by performance disparities across demo…
cs.CV2025
Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study
Max Torop, Masih Eskandar, Nicholas Kurtansky +6
Artificial Intelligence models have demonstrated significant success in diagnosing skin diseases, including cancer, showing the potential to assist clinicians in their analysis. Ho…
eess.IV2020
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein +21
Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algo…