AIMC Topic: Pregnancy Complications

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Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

American journal of public health
OBJECTIVES: To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services.

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment.

Journal of medical systems
The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestation...

Automatic Classification of Structured Product Labels for Pregnancy Risk Drug Categories, a Machine Learning Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
With regular expressions and manual review, 18,342 FDA-approved drug product labels were processed to determine if the five standard pregnancy drug risk categories were mentioned in the label. After excluding 81 drugs with multiple-risk categories, 8...

Pregnancy risk factors in autism: a pilot study with artificial neural networks.

Pediatric research
BACKGROUND: Autism is a multifactorial condition in which a single risk factor can unlikely provide comprehensive explanation for the disease origin. Moreover, due to the complexity of risk factors interplay, traditional statistics is often unable to...

Antidepressant use in late gestation and risk of postpartum haemorrhage: a retrospective cohort study.

BJOG : an international journal of obstetrics and gynaecology
OBJECTIVE: To investigate the association between antidepressant use in late gestation and postpartum haemorrhage (PPH).

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

Health care management science
A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital'...

Artificial intelligence predicts pregnancy complications based on cytokine profiles.

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
BACKGROUND: Early prediction of pregnancy complications is important for adequate and timely prevention, management, and reducing maternal/fetal pathogenesis.

PregAN-NET: Addressing Class Imbalance with GANs in Interpretable Computational Framework for Predicting Safety Profile of Drugs Considering Adverse Reactions During Pregnancy.

Journal of biomedical informatics
Adverse Drug Reactions (ADRs) during pregnancy pose significant risks to both the mother and the fetus. Conventional approaches to predict ADR are inadequate due to ethical restrictions that prevent performing medication studies in pregnant women, le...

Predicting pregnancy-related pelvic girdle pain using machine learning.

Musculoskeletal science & practice
BACKGROUND: Pregnancy-related pelvic girdle pain (PPGP) is a common complication during gestation which negatively influences pregnant women's quality of life. There are numerous risk factors associated with PPGP, however, there is limited informatio...

Effect of artificial intelligence driven therapeutic lifestyle changes (AI-TLC) intervention on health behavior and health among obesity pregnant women in China: a randomized controlled trial protocol.

Frontiers in public health
INTRODUCTION: Obesity has reached epidemic proportions globally, posing significant challenges to public health and economic stability. In China, the prevalence of obesity is increasing rapidly, particularly among pregnant women, who face unique risk...