Reply to the letter to the editor: “Machine learning model for predicting preeclampsia-related adverse outcomes”

Max Hackelöer, Sarosh Rana, Stefan Verlohren

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DOI: 10.1016/j.preghy.2026.101501
Published: 2026-09
Container: Pregnancy Hypertension
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.preghy.2026.101501,
  title = {Reply to the letter to the editor: “Machine learning model for predicting preeclampsia-related adverse outcomes”},
  author = {Max Hackelöer and Sarosh Rana and Stefan Verlohren},
  year = {2026},
  journal = {Pregnancy Hypertension},
  doi = {10.1016/j.preghy.2026.101501},
  url = {https://doi.org/10.1016/j.preghy.2026.101501}
}

RIS

TY  - JOUR
TI  - Reply to the letter to the editor: “Machine learning model for predicting preeclampsia-related adverse outcomes”
AU  - Max Hackelöer
AU  - Sarosh Rana
AU  - Stefan Verlohren
PY  - 2026
JO  - Pregnancy Hypertension
DO  - 10.1016/j.preghy.2026.101501
UR  - https://doi.org/10.1016/j.preghy.2026.101501
ER  -

APA

Hackelöer, M., Rana, S., & Verlohren, S. (2026). Reply to the letter to the editor: “Machine learning model for predicting preeclampsia-related adverse outcomes”. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2026.101501

Source records

crossref · retrieved 2026-09-25T11:55:25.467Z