Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT Examinations-Reference-Cited by-同舟云学术

Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT Examinations

Published:2023-07 Issue:1 Volume:221 Page:124-134
ISSN:0361-803X
Container-title:American Journal of Roentgenology
language:en
Short-container-title:American Journal of Roentgenology

Author:

Pooler B. Dustin¹,Garrett John W.¹,Southard Andrew M.¹,Summers Ronald M.²,Pickhardt Perry J.¹

Affiliation:

1. Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252

2. Department of Radiology and Imaging Sciences, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, NIH Clinical Center, Bethesda, MD

Publisher

American Roentgen Ray Society

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://www.ajronline.org/doi/pdf/10.2214/AJR.22.28745

Reference36 articles.

1. High-performance medicine: the convergence of human and artificial intelligence

2. Machine Learning in Medicine

3. Artificial intelligence in radiology

4. Improved CT-based Osteoporosis Assessment with a Fully Automated Deep Learning Tool

5. Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults

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