Work

Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation

Year: 2022

Type: review

Source: Academic Radiology

DOI: 10.1016/j.acra.2022.09.018

Authors: Erich P. Huang, Gene Pennello, Nandita M. deSouza, Xiaofeng Wang, Andrew J. Buckler, Paul E. Kinahan, Huiman X. Barnhart, Jana G. Delfino, Timothy J. Hall, David L. Raunig, Alexander R. Guimaraes, Nancy A. Obuchowski

Institutions: National Institutes of Health, National Cancer Institute, United States Food and Drug Administration, Center for Devices and Radiological Health, Institute of Cancer Research, Cleveland Clinic, Cleveland Clinic Research, Elucid, University of Washington, Duke University, University of Wisconsin–Madison, Takeda (Japan), Oregon Health & Science University

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: National Institutes of Health

Award: G6374948078

OpenAlex ID: W4306975029

FWCI: 0.339

Cites: 77

Cited by: 10

Related to: 10