Development of non-invasive biomarkers for pre-eclampsia through data-driven cardiovascular network models

Development of non-invasive biomarkers for pre-eclampsia through data-driven cardiovascular network models

Abstract Computational models can be at the basis of new powerful technologies for studying and classifying disorders like pre-eclampsia, where it is difficult to distinguish pre-eclamptic patients from non-pre-eclamptic based on pressure when patients have a track record of hypertension. Computatio...

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Bibliographic Details
Main Authors: Claudia Popp, Jason M. Carson, Alex B. Drysdale, Hari Arora, Edward D. Johnstone, Jenny E. Myers, Raoul van Loon
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Uterine doppler waveforms
Pregnancy
Pulse wave velocity
Hypertension
Machine learning
Clinical diagnosis
Online Access:https://doi.org/10.1038/s41598-024-72832-y
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https://doi.org/10.1038/s41598-024-72832-y

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