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Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions by Tarig Elhakim; Kelly Trinh; Arian Mansur; Christopher Bridge; Dania Daye is a Medicine article available to read on EtoBox.

What is Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions about?

CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation.

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Author

Tarig Elhakim; Kelly Trinh; Arian Mansur; Christopher Bridge; Dania Daye

Publisher

MDPI AG

Published

2023

Language

EN

Field

Medicine (Health Sciences)