AIMC Topic: Stillbirth

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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...
Pregnancy in Obesity Routinely Collected Health Data Uterine Rupture Stillbirth Clinical Decision Rules Obstetric Labor Complications Time Factors Blood Pressure Pre-Eclampsia Maternal Age Postpartum Hemorrhage Hypoxia-Ischemia, Brain Parity Reproducibility of Results Adult Female Premature Birth Humans Machine Learning Retrospective Studies Electronic Health Records Pregnancy
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Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980-2015.

Scientific reports Mar 24, 2020
Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric histo...
Pregnancy Female Prenatal Care Risk Assessment Cohort Studies Socioeconomic Factors Humans Machine Learning Algorithms Reproductive History Western Australia Pregnancy Complications Live Birth Maternal Age Stillbirth
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Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians Jul 18, 2018
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...
Diagnostic Techniques, Obstetrical and Gynecological Infant, Small for Gestational Age Infant Female Severity of Illness Index Gestational Age Prospective Studies Predictive Value of Tests Infant, Newborn Premature Birth Stillbirth Prognosis Male Risk Factors Morbidity Infant, Premature, Diseases Pregnancy Adult Probability Risk Assessment Humans Infant Mortality Machine Learning
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Machine Learning for Predicting Stillbirth: A Systematic Review.

Reproductive sciences (Thousand Oaks, Calif.) May 1, 2025
Stillbirth is a major global issue, with over 5 million cases each year. The multifactorial nature of stillbirth makes it difficult to predict. Artificial intelligence (AI) and machine learning (ML) have the potential to enhance clinical decision-mak...
Female Predictive Value of Tests Stillbirth Humans Machine Learning Pregnancy
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Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes.

Briefings in bioinformatics Sep 2, 2021
OBJECTIVE: Development of novel informatics methods focused on improving pregnancy outcomes remains an active area of research. The purpose of this study is to systematically review the ways that artificial intelligence (AI) and machine learning (ML)...
Live Birth Phenotype Placenta Pregnancy Stillbirth Premature Birth Female Humans Perinatal Care Abortion, Spontaneous Prenatal Care Machine Learning Computational Biology
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Synthetic minority oversampling of vital statistics data with generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2020
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extrem...
ROC Curve Models, Statistical Area Under Curve Humans Neural Networks, Computer Vital Statistics Risk Stillbirth
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