Development and validation of machine learning models for predicting operative duration in assisted reproductive technology procedures

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Publication Details

Journal
BMC Medical Research Methodology
Published
2026-02-03
DOI
https://doi.org/10.1186/s12874-026-02791-7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and validation of machine learning models for predicting operative duration in assisted reproductive technology procedures

Seoyoung Oh, Young Soo Park, Hyo Young Kim
BMC Medical Research Methodology
Artificial Intelligence in Healthcare and Education
article

Development and validation of machine learning models for predicting operative duration in assisted reproductive technology procedures

Seoyoung Oh, Young Soo Park, Hyo Young Kim
article en

Abstract

No abstract available for this paper.
BMC Medical Research MethodologyVol. 26(1)
Kookmin University (KR), Tech University of Korea (KR)
National Research Foundation, National Research Foundation of Korea
Gender equality
Openalex Percentile: Top 70%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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Development and validation of machine learning models for predicting operative duration in assisted reproductive technology procedures — Seoyoung Oh, Young Soo Park, et al. · BMC Medical Research Methodology (2026) | TGRS Research Map | TGRS