๐ NOT FOR MEDICAL USE ๐
Data is here: Pneumonia severity scores for 94 images
- geographic_extent_mean: The extent of lung involvement by ground glass opacity or consolidation for each lung. The total extent score ranged from 0 to 8.
- opacity_mean: The degree of opacity. The total opacity score ranged from 0 to 6.
License: CC BY-SA Creative Commons Attribution-ShareAlike
These are from the follow paper: Cohen, Joseph Paul, et al. Predicting COVID-19 Pneumonia Severity on Chest X-Ray with Deep Learning. Cureus Medical Journal, 10.7759/cureus.9448, http://arxiv.org/abs/2005.11856.
@article{Cohen2020Severity,
title = {Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning},
author = {Cohen, Joseph Paul and Dao, Lan and Morrison, Paul and Roth, Karsten and Bengio, Yoshua and Shen, Beiyi and Abbasi, Almas and Hoshmand-Kochi, Mahsa and Ghassemi, Marzyeh and Li, Haifang and Duong, Tim Q},
journal = {Cureus Medical Journal},
doi = {10.7759/cureus.9448}
url = {https://www.cureus.com/articles/35692-predicting-covid-19-pneumonia-severity-on-chest-x-ray-with-deep-learning},
year = {2020}
}
To run the CLI:
# basic command line predictions
$ python predict_severity.py 2966893D-5DDF-4B68-9E2B-4979D5956C8E.jpeg
geographic_extent (0-8): 5.978744940174467
opacity (0-6): 4.169582852893416
# or to output a saliency map:
$ python predict_severity.py 01E392EE-69F9-4E33-BFCE-E5C968654078.jpeg -saliency_path heatmap.jpg