12 citations · 16 across the 5 of their papers we have counts for
5 papers
Explainable AI as a Double-Edged Sword in Dermatology: The Impact on Clinicians versus The Public
Xuhai Xu, Haoyu Hu, Haoran Zhang +21
Artificial intelligence (AI) is increasingly permeating healthcare, from physician assistants to consumer applications. Since AI algorithm's opacity challenges human interaction, e…
Towards Reliable Dermatology Evaluation Benchmarks
Fabian Gröger, Simone Lionetti, Philippe Gottfrois +6
Benchmark datasets for digital dermatology unwittingly contain inaccuracies that reduce trust in model performance estimates. We propose a resource-efficient data-cleaning protocol…
Augmenting medical image classifiers with synthetic data from latent diffusion models
Luke W. Sagers, James A. Diao, Luke Melas-Kyriazi +6
While hundreds of artificial intelligence (AI) algorithms are now approved or cleared by the US Food and Drugs Administration (FDA), many studies have shown inconsistent generaliza…
Towards Transparency in Dermatology Image Datasets with Skin Tone Annotations by Experts, Crowds, and an Algorithm
Matthew Groh, Caleb Harris, Roxana Daneshjou +2
While artificial intelligence (AI) holds promise for supporting healthcare providers and improving the accuracy of medical diagnoses, a lack of transparency in the composition of d…
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…