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Dania Daye

Harvard University - Department of Radiology

Boston, MA

United States

SCHOLARLY PAPERS

1

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63

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Scholarly Papers (1)

1.

Performance of Automatic Machine Learning versus Radiologists in the Evaluation of Endometrium on Computed Tomography

Number of pages: 43 Posted: 22 Sep 2020
Sun Yat-sen University (SYSU) - Department of Interventional Medicine, Central South University - School of Computer Science and Engineering, Central South University - Department of Radiology, affiliation not provided to SSRN, Brown University - Department of Diagnostic Imaging, Brown University - Department of Diagnostic Imaging, Harvard University - Department of Radiology, University of Pennsylvania - Department of Pathology and Laboratory Medicine, Brown University - Department of Pathology, Harvard University - Department of Radiology, Harvard University - Department of Radiology, Brown University - Department of Diagnostic Imaging, Central South University - School of Computer Science and Engineering, Central South University - Department of Radiology, Central South University - College of Literature and Journalism and Brown University - Department of Diagnostic Imaging
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Abstract:

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endometrial cancer, automatic machine learning, radiomics, computed tomography