23 citations · 48 across the 11 of their papers we have counts for
5 papers · 1 filter
On dataset transferability in medical image classification
Dovile Juodelyte, Enzo Ferrante, Yucheng Lu +3
Current transferability estimation methods designed for natural image datasets are often suboptimal in medical image classification. These methods primarily focus on estimating the…
Exploring connections of spectral analysis and transfer learning in medical imaging
Yucheng Lu, Dovile Juodelyte, Jonathan D. Victor +1
In this paper, we use spectral analysis to investigate transfer learning and study model sensitivity to frequency shortcuts in medical imaging. By analyzing the power spectrum dens…
Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging
Dovile Juodelyte, Yucheng Lu, Amelia Jiménez-Sánchez +3
Transfer learning has become an essential part of medical imaging classification algorithms, often leveraging ImageNet weights. The domain shift from natural to medical images has…
Copycats: the many lives of a publicly available medical imaging dataset
Amelia Jiménez-Sánchez, Natalia-Rozalia Avlona, Dovile Juodelyte +5
Medical Imaging (MI) datasets are fundamental to artificial intelligence in healthcare. The accuracy, robustness, and fairness of diagnostic algorithms depend on the data (and its…
[Citation needed] Data usage and citation practices in medical imaging conferences
Théo Sourget, Ahmet Akkoç, Stinna Winther +5
Medical imaging papers often focus on methodology, but the quality of the algorithms and the validity of the conclusions are highly dependent on the datasets used. As creating data…