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Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study

delete2026-05-14
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OA
AI
O
Ohad Houri
L
Lina Youssef *
F
F. Crovetto
M
Maria Borrell
M
Maddalena Crimella
M
Maria Giulia Ferrante
R
Rommy H. Novoa
I
Irene Casas
N
Noelia Encabo
L
Leticia Benítez
M
Marta Larroya
A
Anna Peguero
E
E. Meler
S
Sara Castro-Barquero
B
Bart Bijnens
F
Francesc Figueras
E
Eduard Gratacos
G
Gabriel Bernardino
F
F. Crispi
DOI:10.1111/1471-0528.70262delete
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Abstract

Abstract

En 中文
To explore clinically meaningful phenotypes of preeclampsia using unsupervised machine learning.
Keywords:
cluster analysis
preeclampsia
pregnancy complications
unsupervised machine learning
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Journal

B
bjog: an international journal of obstetrics & gynaecology
IF:
0
Papers:
148
Citations:
0

Organization

U
universitat pompeu fabra
Scholars:
298
Papers: 164
Citations: 0
I
icrea
Scholars:
100
Papers: 86
Citations: 0
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