Search Results for author: Seth J. Berkowitz

Found 2 papers, 1 papers with code

Deep Learning to Quantify Pulmonary Edema in Chest Radiographs

1 code implementation13 Aug 2020 Steven Horng, Ruizhi Liao, Xin Wang, Sandeep Dalal, Polina Golland, Seth J. Berkowitz

Results: The area under the receiver operating characteristic curve (AUC) for differentiating alveolar edema from no edema was 0. 99 for the semi-supervised model and 0. 87 for the pre-trained models.

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

no code implementations21 Jan 2019 Alistair E. W. Johnson, Tom J. Pollard, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G. Mark, Seth J. Berkowitz, Steven Horng

Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation.

Cannot find the paper you are looking for? You can Submit a new open access paper.