Artificial Intelligence for the Prediction of Preeclampsia: Current Evidence, Comparison with Conventional Screening Models, and Future Perspectives
- DOI
- 10.3390/diagnostics16182963
- Published
- 2026-09-13
- Container
- Diagnostics
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/diagnostics16182963,
title = {Artificial Intelligence for the Prediction of Preeclampsia: Current Evidence, Comparison with Conventional Screening Models, and Future Perspectives},
author = {Maria Fanaki and Dimitrios Baroutis and Panagiotis Antsaklis and Georgios Daskalakis and Vasileios Pergialiotis},
year = {2026},
journal = {Diagnostics},
doi = {10.3390/diagnostics16182963},
url = {https://doi.org/10.3390/diagnostics16182963}
}RIS
TY - JOUR TI - Artificial Intelligence for the Prediction of Preeclampsia: Current Evidence, Comparison with Conventional Screening Models, and Future Perspectives AU - Maria Fanaki AU - Dimitrios Baroutis AU - Panagiotis Antsaklis AU - Georgios Daskalakis AU - Vasileios Pergialiotis PY - 2026 JO - Diagnostics DO - 10.3390/diagnostics16182963 UR - https://doi.org/10.3390/diagnostics16182963 ER -
APA
Fanaki, M., Baroutis, D., Antsaklis, P., Daskalakis, G., & Pergialiotis, V. (2026). Artificial Intelligence for the Prediction of Preeclampsia: Current Evidence, Comparison with Conventional Screening Models, and Future Perspectives. Diagnostics. https://doi.org/10.3390/diagnostics16182963
Source records
- crossref · retrieved 2026-09-27T11:21:27.623Z