This paper is in the following e-collection/theme issue:

Artificial Intelligence (1409) Obstetrics, Gynecology, and Reproductive Medicine (232) Decision Support for Health Professionals (1203) Development and Evaluation of Research Methods, Instruments and Tools (503) Imaging Informatics (198) Machine Learning (1491)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52637, first published .
Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Authors of this article:

Hyung Min Kim1 Author Orcid Image ;   Hyoeun Kang1 Author Orcid Image ;   Chaeyoon Lee1 Author Orcid Image ;   Jong Hyuk Park2 Author Orcid Image ;   Mi Kyung Chung3 Author Orcid Image ;   Miran Kim4 Author Orcid Image ;   Na Young Kim5 Author Orcid Image ;   Hye Jun Lee6 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Sergeev S, Diakova I, Nadirashvili L. Neural networks pipeline for quality management in IVF laboratory. Journal of IVF-Worldwide 2024;2(4) View