Comparison of predictive models for cumulative live birth rate after treatment with ART-Reference-Cited by-同舟云学术

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Comparison of predictive models for cumulative live birth rate after treatment with ART

Published:2022-08 Issue:2 Volume:45 Page:246-255
ISSN:1472-6483
Container-title:Reproductive BioMedicine Online
language:en
Short-container-title:Reproductive BioMedicine Online

Author:

Bardet Léna,Excoffier Jean-Baptiste^ORCID,Salaun-Penquer Noemie,Ortala Matthieu,Pasquier Maud,Mathieu d'Argent Emmanuelle,Massin Nathalie

Funder

Ferring Pharmaceuticals

Merck

Meso Scale Diagnostics

Publisher

Elsevier BV

Subject

Developmental Biology,Reproductive Medicine,Obstetrics and Gynecology

Reference33 articles.

1. Interpretable Machine Learning in Healthcare;Ahmad,2018

2. XGBoost: A Scalable Tree Boosting System;Chen,2016

3. Evaluating prediction models in reproductive medicine;Coppus;Human Reproduction,2009

4. Predicting the chance of live birth for women undergoing IVF: a novel pretreatment counselling tool;Dhillon;Human Reproduction,2016

5. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis;Harrell,2015

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1. Factors affecting biochemical pregnancy loss (BPL) in preimplantation genetic testing for aneuploidy (PGT-A) cycles: machine learning-assisted identification;Reproductive Biology and Endocrinology;2024-08-08

2. Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications;Mayo Clinic Proceedings: Digital Health;2024-08

3. Immunological parameters of maternal peripheral blood as predictors of future pregnancy outcomes in patients with unexplained recurrent pregnancy loss;Acta Obstetricia et Gynecologica Scandinavica;2024-03-21

4. Reproductive plans and knowledge of assisted reproductive techniques among lesbian women: an international survey study;JBRA Assisted Reproduction;2023

5. Development of a Diagnosis Grading System for Patients Undergoing Intrauterine Inseminations: A Machine-learning Perspective;2022-07-19

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