787 citations · 989 across the 6 of their papers we have counts for
6 papers
Detecting Shortcut Learning for Fair Medical AI using Shortcut Testing
Alexander Brown, Nenad Tomasev, Jan Freyberg +3
Machine learning (ML) holds great promise for improving healthcare, but it is critical to ensure that its use will not propagate or amplify health disparities. An important step is…
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo +14
Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings. Importantl…
Supervised Transfer Learning at Scale for Medical Imaging
Basil Mustafa, Aaron Loh, Jan Freyberg +12
Transfer learning is a standard technique to improve performance on tasks with limited data. However, for medical imaging, the value of transfer learning is less clear. This is lik…
Addressing the Real-world Class Imbalance Problem in Dermatology
Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan +2
Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes. This is espe…
DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Amirata Ghorbani, Vivek Natarajan, David Coz +1
Despite the recent success in applying supervised deep learning to medical imaging tasks, the problem of obtaining large and diverse expert-annotated datasets required for the deve…
A deep learning system for differential diagnosis of skin diseases
Yuan Liu, Ayush Jain, Clara Eng +19
Skin conditions affect an estimated 1.9 billion people worldwide. A shortage of dermatologists causes long wait times and leads patients to seek dermatologic care from general prac…