Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session H71: Poster Session I (2:00pm - 4:00pm)
2:00 PM,
Tuesday, March 16, 2021
Abstract: H71.00115 : Performance and Robustness of Machine Learning-based Radiomic COVID-19 Severity Prediction
Presenter:
Zan Klanecek
(Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia)
Authors:
Zan Klanecek
(Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia)
Shotaro Naganawa
(Department of Radiology, University of Michigan, Ann Arbor, MI, U.S.A)
John Kim
(Department of Radiology, University of Michigan, Ann Arbor, MI, U.S.A)
Luciano Rivetti
(FUESMEN-FADESA, Mendoza, Argentina)
Andrej Studen
(Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia)
Stephen S.F. Yip
(Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, U.S.A)
Robert Jeraj
(Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, U.S.A)
The dataset provider and radiologist used imaging and clinical data to classify patients as mild, moderate, or severe. For each CT, 107 radiomic features (RF) were extracted. Selected RF were combined into a LR model for distinguishing severe from mild and moderate cases. The models were trained and validated with AUC on both observers’ classifications. Sensitivity analysis of imaging parameters and cross-validation (CV) on the inter-observer classifications determined model robustness.
A single RF (gray-level co-cccurrence matrix-Correlation) was sufficient to predict mild from severe C19 with AUCprovider=0.85 and AUCradiologist=0.74 (CV yielded AUCs≈0.80). In predicting moderate from severe C19, first-order-Median RF alone had sufficient predictive power of AUCprovider=0.65. The AUCradiologist increased to 0.66 as the number of RF grew to 5 (CV yielded AUCs≈0.62). Study suggests that RF may be useful for identification of severe C19 cases.
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700