Open AccessAutomated Measurements of Muscle Mass Using Deep Learning Can Predict Clinical Outcomes in Patients With Liver Disease
Author(s) -
Nicholas Wang,
Peng Zhāng,
Elliot B. Tapper,
Sameer D. Saini,
Stewart C. Wang,
Grace L. Su
Publication year - 2020
Publication title -
the american journal of gastroenterology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.907
H-Index - 252
eISSN - 1572-0241
pISSN - 0002-9270
DOI - 10.14309/ajg.0000000000000662
Subject(s) - medicine , intraclass correlation , cohort , cirrhosis , artificial intelligence , machine learning , radiology , computer science , clinical psychology , psychometrics
There is increasing recognition of the central role of muscle mass in predicting clinical outcomes in patients with liver disease. Muscle size can be extracted from computed tomography (CT) scans, but clinical implementation will require increased automation. We hypothesize that we can achieve this by using artificial intelligence.