An integrated optimization and deep learning pipeline for predicting live birth success in IVF using feature optimization and transformer-based models

20255 citationsJournal Articlehybrid Open Access

Authors

Arezoo Borji · Danube Private University

Hossam Haick · Technion – Israel Institute of Technology

Birgit Pohn · Danube Private University

Antonia Graf · Danube Private University

Jana Zakall · Danube Private University

S M Ragib Shahriar Islam · Austrian Center for Medical Innovation and Technology

Gernot Kronreif

Abstract

With the accuracy and interpretability, this study develops a strong AI pipeline for predicting live birth outcomes in IVF. This study establishes a highly accurate AI pipeline for predicting live birth outcomes in IVF, demonstrating its potential to enhance personalized fertility treatments.

Topics & Keywords

Assisted Reproductive Technology and Twin Pregnancy Pregnancy and preeclampsia studies Insurance, Mortality, Demography, Risk Management

Publication Details

Published in: Computer Methods and Programs in Biomedicine

Volume 271, pp. 108979-108979

DOI: 10.1016/j.cmpb.2025.108979

Field-Weighted Citation Impact: 20.09

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An integrated optimization and deep learning pipeline for predicting live birth success in IVF using feature optimization and transformer-based models

Authors

Abstract

Topics & Keywords

Publication Details