Feasibility of deep learning for predicting live birth from a blastocyst image in patients classified by age

Autor:	Yasunari Miyagi, Toshihiro Habara, Rei Hirata, Nobuyoshi Hayashi
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	artificial intelligence blastocyst deep learning live birth neural network Diseases of the endocrine glands. Clinical endocrinology RC648-665 Reproduction QH471-489
Zdroj:	Reproductive Medicine and Biology, Vol 18, Iss 2, Pp 190-203 (2019)
Druh dokumentu:	article
ISSN:	1447-0578 1445-5781
DOI:	10.1002/rmb2.12266
Popis:	Abstract Purpose To identify artificial intelligence (AI) classifiers in images of blastocysts to predict the probability of achieving a live birth in patients classified by age. Results are compared to those obtained by conventional embryo (CE) evaluation. Methods A total of 5691 blastocysts were retrospectively enrolled. Images captured 115 hours after insemination (or 139 hours if not yet large enough) were classified according to maternal age as follows:
Databáze:	Directory of Open Access Journals
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