Chappell, Joanna;
Mufti, Nada;
Irzan, Hassna;
O'Brien, Pat;
Attilakos, George;
Sokolska, M;
Narayanan, P;
... Melbourne, Andrew; + view all
(2023)
Feature Selection To Facilitate Surgical Planning From MRI Of Placenta Accreta Spectrum Disorder.
In:
Proceedings of the 2023 ISMRM & ISMRT Annual Meeting & Exhibition.
(pp. pp. 1-6).
International Society for Magnetic Resonance in Medicine
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Abstract
Feature Selection Models provide a ranking of pathological MRI markers able to predict the outcome of Placenta Accreta Spectrum Disorder, which could be used to aid in clinical decision-making and improve maternal outcome. The potential being to reduce the workload of radiologists by establishing the most clinically relevant pathological MRI markers that predict outcome. Our results found three pathological markers to have the highest ranking to the outcomes with an average accuracy of 75% using a Random Forest Selection Model and Boruta algorithm.
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