Machine learning applications in placenta accreta spectrum disorders

Machine learning applications in placenta accreta spectrum disorders

This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that ut...

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Bibliographic Details
Main Authors: Mahsa Danaei, Maryam Yeganegi, Sepideh Azizi, Fatemeh Jayervand, Seyedeh Elham Shams, Mohammad Hossein Sharifi, Reza Bahrami, Ali Masoudi, Amirhossein Shahbazi, Amirmasoud Shiri, Heewa Rashnavadi, Kazem Aghili, Hossein Neamatzadeh
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:European Journal of Obstetrics & Gynecology and Reproductive Biology: X
Subjects:
Machine Learning
Radiomics
Placenta Accreta Spectrum
Diagnostic Methods
Surgical Planning
Predictive Models
Online Access:http://www.sciencedirect.com/science/article/pii/S2590161324000826
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