Deep learning classification integrating embryo images with associated clinical information from ART cycles

Deep learning classification integrating embryo images with associated clinical information from ART cycles

Abstract An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enabling accurate prediction of clinical pregnancy outcomes in single embryo transfer procedures. Three AI models were developed, trained, and te...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohamed Salih, Christopher Austin, Krishna Mantravadi, Eva Seow, Sutthipat Jitanantawittaya, Sandeep Reddy, Beverley Vollenhoven, Hamid Rezatofighi, Fabrizzio Horta
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
IVF/ICSI outcome
Infertility
Embryo selection
Embryology
Deep learning
Online Access:https://doi.org/10.1038/s41598-025-02076-x
Tags: Add Tag
No Tags, Be the first to tag this record!
Login for hold and recall information

Internet

https://doi.org/10.1038/s41598-025-02076-x

Similar Items