1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 1 cited
Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT
Jacopo Teneggi, Paul H. Yi, Jeremias Sulam
Modern machine learning pipelines, in particular those based on deep learning (DL) models, require large amounts of labeled data. For classification problems, the most common learn…
eess.IV2022
From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning
Pranav Kulkarni, Adway Kanhere, Paul H. Yi +1
Chest X-ray (CXR) datasets hosted on Kaggle, though useful from a data science competition standpoint, have limited utility in clinical use because of their narrow focus on diagnos…