ivf_lbr_prediction: Machine Learning Prediction of Live Birth After IVF Using Adenomyosis Features

Björnsson, Ola, Sara Alson
2025 · doi:10.5281/zenodo.17715463 · W7106668813
other OA: green CC0
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This study developed and evaluated machine learning models to predict live birth after IVF by analyzing ultrasound features of adenomyosis according to MUSA criteria.

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Abstract

XGBoost-based machine learning models for predicting live birth rates following in vitro fertilization (IVF) treatment, incorporating ultrasound features of adenomyosis based on the Morphological Uterus Sonographic Assessment (MUSA) criteria. This repository contains code for hyperparameter optimization using Optuna, cross-validation, model evaluation, and feature importance analysis using SHAP values.
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Published November 25, 2025 | Version v1.0.0 Software Open ivf_lbr_prediction: Machine Learning Prediction of Live Birth After IVF Using Adenomyosis Features Authors/Creators - 1. Department of Energy Sciences, Faculty of Engineering, Lund University, Lund, Sweden - 2. Obstetric, Gynecological and Prenatal Ultrasound research, Department of Clinical Sciences, Malmö, Lund University, Sweden Description XGBoost-based machine learning models for predicting live birth rates following in vitro fertilization (IVF) treatment, incorporating ultrasound features of adenomyosis based on the Morphological Uterus Sonographic Assessment (MUSA) criteria. This repository contains code for hyperparameter optimization using Optuna, cross-validation, model evaluation, and feature importance analysis using SHAP values. Files F-Ursus/ivf_lbr_prediction-v1.0.0.zip Files (32.9 kB) | Name | Size | Download all | |---|---|---| | md5:b5fe8ff6176de76c56086b58e05bc152 | 32.9 kB | Preview Download | Additional details Related works - Is supplement to - Software: https://github.com/F-Ursus/ivf_lbr_prediction/tree/v1.0.0 (URL) Software - Repository URL - https://github.com/F-Ursus/ivf_lbr_prediction

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Outcome instruments

MUSA

Condition tags

adenomyosis

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last seen: 2026-06-04T00:00:01.174412+00:00
License: CC0 · commercial use OK