Work

Performance of automatic machine learning versus radiologists in the evaluation of endometrium on computed tomography

Year: 2021

Type: article

Source: Abdominal Radiology

DOI: 10.1007/s00261-021-03210-9

Authors: Dan Li, Rong Hu, Jing Wu, Shixin Liu, Subhanik Purkayastha, Michael Atalay, Dania Daye, Paul J. Zhang, Shaolei Lu, Ken Chang, Raymond Y. Huang, Michael D. Beland, Beiji Zou, Zishu Zhang, Chengzhang Zhu, Harrison X. Bai

Institutions: Sun Yat-sen University, Sixth Affiliated Hospital of Sun Yat-sen University, Central South University, Second Xiangya Hospital of Central South University, Brown University, Hospital of the University of Pennsylvania, Harvard University, Rhode Island Hospital, University of Pennsylvania

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funder: Foundation for the National Institutes of Health

Award: G1449562455

OpenAlex ID: W3183975690

FWCI: 0.396

Cites: 64

Cited by: 5

Related to: 10