Predicting clinical pregnancy using clinical features and machine learning algorithms in in vitro fertilization
- DOI
- 10.1371/journal.pone.0267554
- Published
- 2022-06-08
- Container
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0267554,
title = {Predicting clinical pregnancy using clinical features and machine learning algorithms in in vitro fertilization},
author = {Cheng-Wei Wang and Chao-Yang Kuo and Chi-Huang Chen and Yu-Hui Hsieh and Emily Chia-Yu Su},
year = {2022},
journal = {PLOS ONE},
doi = {10.1371/journal.pone.0267554},
url = {https://doi.org/10.1371/journal.pone.0267554}
}RIS
TY - JOUR TI - Predicting clinical pregnancy using clinical features and machine learning algorithms in in vitro fertilization AU - Cheng-Wei Wang AU - Chao-Yang Kuo AU - Chi-Huang Chen AU - Yu-Hui Hsieh AU - Emily Chia-Yu Su PY - 2022 JO - PLOS ONE DO - 10.1371/journal.pone.0267554 UR - https://doi.org/10.1371/journal.pone.0267554 ER -
APA
Wang, C., Kuo, C., Chen, C., Hsieh, Y., & Su, E. C. (2022). Predicting clinical pregnancy using clinical features and machine learning algorithms in in vitro fertilization. PLOS ONE. https://doi.org/10.1371/journal.pone.0267554
Source records
- crossref · retrieved 2026-11-10T19:54:13.995Z