10 citations · 19 across the 4 of their papers we have counts for
4 papers
Critical Evaluation of Artificial Intelligence as Digital Twin of Pathologist for Prostate Cancer Pathology
Okyaz Eminaga, Mahmoud Abbas, Christian Kunder +10
Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading pat…
BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors
Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang +12
Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples…
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations
Bryan Gopal, Ryan W. Han, Gautham Raghupathi +3
We propose 3KG, a physiologically-inspired contrastive learning approach that generates views using 3D augmentations of the 12-lead electrocardiogram. We evaluate representation qu…
Deep Learning for Prostate Pathology
Okyaz Eminaga, Yuri Tolkach, Christian Kunder +13
The current study detects different morphologies related to prostate pathology using deep learning models; these models were evaluated on 2,121 hematoxylin and eosin (H&E) stain hi…