Deep Learning to Predicting Live Births and Aneuploid Miscarriages from Images of Blastocysts Combined with Maternal Age
Journal Title: International Journal of Bioinformatics and Intelligent Computing - Year 2022, Vol 1, Issue 1
Abstract
Objectives: Making an artificial intelligence (AI) classifier that uses the maternal age and an image of the implanted blastocyst to determine the probability of getting a live birth. Methods: The dataset comprised maternal age data and 407 images of blastocysts which led to live births and 246 images of blastocysts which led to aneuploid miscarriages, matched for maternal age. An AI system using deep learning was developed for predicting the classification and probability of a live birth. Results: The accuracy, sensitivity, specificity, and positive and negative predictive values of the developed AI classifier were 0.75, 0.82, 0.64, 0.79, and 0.68, respectively. The area under the curve was 0.73 ± 0.04 (mean ± standard error). Conclusions: A classifier using AI for a blastocyst image combined with the maternal age showed potential in determining the probability of a live birth.
Authors and Affiliations
Yasunari Miyagi, Toshihiro Habara, Rei Hirata, Nobuyoshi Hayashi
Keywords
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- EP ID EP724391
- DOI https://doi.org/10.61797/ijbic.v1i1.132
- Views 69
- Downloads 0
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