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Pregnancy

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Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks.

Medical image analysis
In this work, we present a novel gaze-assisted natural language processing (NLP)-based video captioning model to describe routine second-trimester fetal ultrasound scan videos in a vocabulary of spoken sonography. The primary novelty of our multi-mod...

Prediction of placenta accreta spectrum by combining deep learning and radiomics using T2WI: a multicenter study.

Abdominal radiology (New York)
PURPOSE: To achieve prenatal prediction of placenta accreta spectrum (PAS) by combining clinical model, radiomics model, and deep learning model using T2-weighted images (T2WI), and to objectively evaluate the performance of the prediction through mu...

Development and validation of a machine-learning algorithm to predict the relevance of scientific articles within the field of teratology.

Reproductive toxicology (Elmsford, N.Y.)
The Dutch Teratology Information Service Lareb counsels healthcare professionals and patients about medication use during pregnancy and lactation. To keep the evidence up to date, employees perform a standardized weekly PubMed query where relevant li...

Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate Recordings.

Biosensors
We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analy...

Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Automated segmentation of the placenta by MRI in early pregnancy may help predict normal and aberrant placenta function, which could improve the efficiency of placental assessment and the prediction of pregnancy outcomes. An automated seg...

Toxicity, genotoxicity, and carcinogenicity of 2-methylfuran in a 90-day comprehensive toxicity study in gpt delta rats.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
2-Methylfuran (2-MF) exists naturally in foods and is used as a flavoring agent. Furan, the core structure of 2-MF, possesses hepatocarcinogenicity in rodents. Accumulation of toxicological information on furan derivatives is needed to elucidate thei...

A Machine Learning-Based Intrauterine Growth Restriction (IUGR) Prediction Model for Newborns.

Indian journal of pediatrics
Intrauterine growth restriction (IUGR) is a condition in which the fetal weight is below the 10th percentile for its gestational age. Prenatal exposure to metals can cause a decrease in fetal growth during gestation thereby reducing birth weight. The...

An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos.

Reproductive biomedicine online
RESEARCH QUESTION: Can better methods be developed to evaluate the performance and characteristics of an artificial intelligence model for evaluating the likelihood of clinical pregnancy based on analysis of day-5 blastocyst-stage embryos, such that ...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can hel...