AIMC Topic: Prenatal Care
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Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape.
Gates open research
Oct 29, 2024
BACKGROUND: The WHO's recommendations on antenatal care underscore the need for ultrasound assessment during pregnancy. Given that maternal and perinatal mortality remains unacceptably high in underserved regions, these guidelines are imperative for ...
Artificial Intelligence-Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review.
Journal of medical Internet research
Sep 16, 2024
BACKGROUND: Despite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferation of artificial intelligence (AI) over the last decade, it remains understudied regarding the role of AI in CDSS specialize...
Machine learning, advanced data analysis, and a role in pregnancy care? How can we help improve preeclampsia outcomes?
Pregnancy hypertension
Jun 13, 2024
The value of machine learning capacity in maternal health, and in particular prediction of preeclampsia will only be realised when there are high quality clinical data provided, representative populations included, different health systems and models...
High-resolution mapping of essential maternal and child health service coverage in Nigeria: a machine learning approach.
BMJ open
Jun 10, 2024
BACKGROUND: National-level coverage estimates of maternal and child health (MCH) services mask district-level and community-level geographical inequities. The purpose of this study is to estimate grid-level coverage of essential MCH services in Niger...
Real-time Classification of Fetal Status Based on Deep Learning and Cardiotocography Data.
Journal of medical systems
Aug 3, 2023
This study uses convolutional neural networks (CNNs) and cardiotocography data for the real-time classification of fetal status in the mobile application of a pregnant woman and the computer server of a data expert at the same time (The sensor is con...
Deep learning model for predicting gestational age after the first trimester using fetal MRI.
European radiology
Apr 14, 2021
OBJECTIVES: To evaluate a deep learning model for predicting gestational age from fetal brain MRI acquired after the first trimester in comparison to biparietal diameter (BPD).
Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study.
BMC pregnancy and childbirth
Mar 12, 2021
BACKGROUND: Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the f...
Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence.
Journal of pharmacokinetics and pharmacodynamics
Apr 11, 2020
The role of artificial intelligence (AI) in healthcare for pregnant women. To assess the role of AI in women's health, discover gaps, and discuss the future of AI in maternal health. A systematic review of English articles using EMBASE, PubMed, and S...
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...
[Artificial intelligence and fetal imaging: What are we talking about?].
Gynecologie, obstetrique, fertilite & senologie
Oct 4, 2019
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