AIMC Topic: Pre-Eclampsia

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Artificial intelligence: The current state of affairs for AI in pregnancy and labour.

Journal of gynecology obstetrics and human reproduction Dec 31, 2020
Humans Risk Assessment Cardiotocography Pre-Eclampsia Pregnancy Complications Artificial Intelligence Pregnancy Female Premature Birth Postnatal Care Obstetric Labor, Premature Pregnancy, Ectopic Obstetric Labor Complications
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Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology Oct 22, 2020
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...
Routinely Collected Health Data Uterine Rupture Obstetric Labor Complications Stillbirth Clinical Decision Rules Pregnancy in Obesity Adult Time Factors Blood Pressure Pre-Eclampsia Maternal Age Postpartum Hemorrhage Hypoxia-Ischemia, Brain Female Premature Birth Parity Reproducibility of Results Retrospective Studies Electronic Health Records Pregnancy Humans Machine Learning
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Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia.

EBioMedicine Apr 10, 2020
BACKGROUND: We developed and validated an artificial intelligence (AI)-assisted prediction of preeclampsia applied to a nationwide health insurance dataset in Indonesia.
Blood Pressure Pregnancy Indonesia Humans Demography Machine Learning Pre-Eclampsia Female National Health Programs Medical History Taking Adult Models, Statistical
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Prediction model development of late-onset preeclampsia using machine learning-based methods.

PloS one Aug 23, 2019
Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the lack of effective preventive measures, its prediction is essential to its prompt management. This study aimed to develop models using machine learning...
Logistic Models Support Vector Machine Pregnancy Trimester, Third Machine Learning Pre-Eclampsia Bayes Theorem Humans Pregnancy Age of Onset Pregnancy Trimester, Second Female Gestational Age Adult
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Placental CD4 T cells isolated from preeclamptic women cause preeclampsia-like symptoms in pregnant nude-athymic rats.

Pregnancy hypertension Nov 2, 2018
Preeclampsia (PE), new onset hypertension during pregnancy, is associated with a proinflammatory profile compared to normal pregnancy (NP). We hypothesize that CD4 T cells from PE patient placentas cause PE symptoms during pregnancy compared to those...
Rats, Nude Vascular Endothelial Growth Factor Receptor-1 Pre-Eclampsia Arterial Pressure Enzyme-Linked Immunosorbent Assay Real-Time Polymerase Chain Reaction Female Humans Placentation Disease Models, Animal Interleukin-17 Young Adult Tumor Necrosis Factor-alpha Placenta Rats Pregnancy Adult CD4-Positive T-Lymphocytes Animals
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Statistical and artificial neural network-based analysis to understand complexity and heterogeneity in preeclampsia.

Computational biology and chemistry May 16, 2018
Preeclampsia is a pregnancy associated disease. It is characterized by high blood pressure and symptoms that are indicative of damage to other organ systems, most often involving the liver and kidneys. If left untreated, the condition could be fatal ...
Female Pre-Eclampsia Humans Neural Networks, Computer Machine Learning Pregnancy
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The Pre-Eclampsia Ontology: A Disease Ontology Representing the Domain Knowledge Specific to Pre-Eclampsia.

PloS one Oct 27, 2016
Pre-eclampsia (PE) is a clinical syndrome characterized by new-onset hypertension and proteinuria at ≥20 weeks of gestation, and is a leading cause of maternal and perinatal morbidity and mortality. Previous studies have gathered abundant data about ...
Humans Pregnancy Female Pre-Eclampsia Biological Ontologies Terminology as Topic
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Temporal validation of machine learning models for pre-eclampsia prediction using routinely collected maternal characteristics: A validation study.

Computers in biology and medicine Jun 1, 2025
BACKGROUND: Pre-eclampsia (PE) contributes to more than one-fourth of all maternal deaths and half a million newborn deaths worldwide every year. Early screening and interventions can reduce PE incidence and related complications. We aim to 1) tempor...
Logistic Models Australia Pre-Eclampsia Humans Female Machine Learning Adult Pregnancy ROC Curve
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Predictive Models Using Machine Learning to Identify Fetal Growth Restriction in Patients With Preeclampsia: Development and Evaluation Study.

Journal of medical Internet research May 27, 2025
BACKGROUND: Fetal growth restriction (FGR) is a common complication of preeclampsia. FGR in patients with preeclampsia increases the risk of neonatal-perinatal mortality and morbidity. However, previous prediction methods for FGR are class-biased or ...
Humans Adult Case-Control Studies Pre-Eclampsia Fetal Growth Retardation Machine Learning Retrospective Studies Pregnancy Female
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Text phrase-mining in identifying and classifying maternal proteins and genes across preeclampsia and similar pathologies.

Physiological reports Mar 1, 2025
This study aims to demonstrate that text phrase-mining and natural language processing (NLP) can annotate huge quantities of obstetrics textual data for the discovery and evaluation of maternal protein/gene (MPG)-disease interactions involved in the ...
Natural Language Processing Pre-Eclampsia Humans Pregnancy Proteins Pregnancy Data Mining Female
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