1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Beyond validation loss: Clinically-tailored optimization metrics improve a model's clinical performance
Charles B. Delahunt, Courosh Mehanian, Daniel E. Shea +1
A key task in ML is to optimize models at various stages, e.g. by choosing hyperparameters or picking a stopping point. A traditional ML approach is to use validation loss, i.e. to…
eess.IV2023★ 1 cited
How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound
Menghan Yu, Sourabh Kulhare, Courosh Mehanian +5
Acquiring large quantities of data and annotations is known to be effective for developing high-performing deep learning models, but is difficult and expensive to do in the healthc…