Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study
Amogh Hiremath(Ohio Department of Health), Anant Madabhushi(Emory University), Rakesh Shiradkar(Emory University), Cheng Lu(Guangdong Academy of Medical Sciences), Amit Gupta(University of Washington), Pingfu Fu(Medical College of Wisconsin), Kaustav Bera(University Hospitals of Cleveland), Robert Gilkeson(University Hospitals of Cleveland), Lei Yuan(Max Planck Institute of Molecular Cell Biology and Genetics), Keith B. Armitage(University Hospitals of Cleveland), Vidya Sankar Viswanathan(Case Western Reserve University), Mengyao Ji(Wuhan University)
Cited by 8
Related Papers
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
|Nature Reviews Clinical Oncology|2021|810
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update
|Radiology Artificial Intelligence|2024|406
Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer
|Cancer Immunology Research|2019|313
Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer
|npj Breast Cancer|2020|208
Inhalation Toxicity and Lung Toxicokinetics of C60 Fullerene Nanoparticles and Microparticles
|Toxicological Sciences|2007|201