Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions.
Publication/Presentation Date
3-3-2023
Abstract
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.
Volume
13
Issue
5
ISSN
2075-4418
Published In/Presented At
Elhakim, T., Trinh, K., Mansur, A., Bridge, C., & Daye, D. (2023). Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions. Diagnostics (Basel, Switzerland), 13(5), 968. https://doi.org/10.3390/diagnostics13050968
Disciplines
Medicine and Health Sciences
PubMedID
36900112
Department(s)
Fellows and Residents
Document Type
Article
