肌萎缩
叙述性评论
电流(流体)
叙述的
医学
心理学
老年学
重症监护医学
内科学
工程类
哲学
语言学
电气工程
作者
Miłosz Rozynek,Iwona Kucybała,Andrzej Urbanik,Wadim Wojciechowski
出处
期刊:Nutrition
[Elsevier]
日期:2021-09-01
卷期号:89: 111227-111227
被引量:19
标识
DOI:10.1016/j.nut.2021.111227
摘要
Sarcopenia is a muscle disease which previously was associated only with aging, but in recent days it has been gaining more attention for its predictive value in a vast range of conditions and its potential link with overall health. Up to this point, evaluating sarcopenia with imaging methods has been time-consuming and dependent on the skills of the physician. The solution for this problem may be found in artificial intelligence, which may assist radiologists in repetitive tasks such as muscle segmentation and body-composition analysis. The major aim of this review was to find and present the current status and future perspectives of artificial intelligence in the imaging of sarcopenia. We searched the PubMed database to find articles concerning the use of artificial intelligence in diagnostic imaging and especially in body-composition analysis in the context of sarcopenia. We found that artificial-intelligence systems could potentially help with evaluating sarcopenia and better predicting outcomes in a vast range of clinical situations, which could get us closer to the true era of precision medicine. • Sarcopenia has an impact on outcomes in various diseases, not only in elderly people. • Artificial intelligence could be used to help evaluate sarcopenia. • Artificial-intelligence systems can alter the clinical importance of imaging modalities in diagnosing sarcopenia. • Automated methods in the evaluation of sarcopenia can potentially give us more information about patients and make clinical practice more tailored.
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