AIMC Topic: Pregnancy
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Machine Learning (ML) based-method applied in recurrent pregnancy loss (RPL) patients diagnostic work-up: a potential innovation in common clinical practice.
Scientific reports
May 14, 2020
RPL is a very debated condition, in which many issues concerning definition, etiological factors to investigate or therapies to apply are still controversial. ML could help clinicians to reach an objectiveness in RPL classification and access to care...
Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.
Sensors (Basel, Switzerland)
May 11, 2020
Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors su...
Deep learning-based monocular placental pose estimation: towards collaborative robotics in fetoscopy.
International journal of computer assisted radiology and surgery
Apr 30, 2020
PURPOSE: Twin-to-twin transfusion syndrome (TTTS) is a placental defect occurring in monochorionic twin pregnancies. It is associated with high risks of fetal loss and perinatal death. Fetoscopic elective laser ablation (ELA) of placental anastomoses...
FetNet: a recurrent convolutional network for occlusion identification in fetoscopic videos.
International journal of computer assisted radiology and surgery
Apr 29, 2020
PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgery for the treatment of twin-to-twin transfusion syndrome (TTTS). By using a lens/fibre-optic scope, inserted into the amniotic cavity, the abnormal placental vascular anastomose...
FF-QuantSC: accurate quantification of fetal fraction by a neural network model.
Molecular genetics & genomic medicine
Apr 13, 2020
BACKGROUND: Noninvasive prenatal testing (NIPT) is one of the most commonly employed clinical measures for screening of fetal aneuploidy. Fetal Fraction (ff) has been demonstrated to be one of the key factors affecting the performance of NIPT. Accura...
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...
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.
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...
Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning.
Scientific reports
Mar 10, 2020
Assessing the viability of a blastosyst is still empirical and non-reproducible nowadays. We developed an algorithm based on artificial vision and machine learning (and other classifiers) that predicts pregnancy using the beta human chorionic gonadot...
Latent Phase Identification of High-Frequency Micro-Scale Gamma Spike Transients in the Hypoxic Ischemic EEG of Preterm Fetal Sheep Using Spectral Analysis and Fuzzy Classifiers.
Sensors (Basel, Switzerland)
Mar 5, 2020
Premature babies are at high risk of serious neurodevelopmental disabilities, which in many cases are related to perinatal hypoxic-ischemic encephalopathy (HIE). Studies of neuroprotection in animal models consistently suggest that treatment must be ...
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