AIMC Topic: Pregnancy

Clear Filters Showing 991 to 1000 of 1220 articles

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach.

Systems biology in reproductive medicine
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this s...

Predictive efficacy of machine-learning algorithms on intrahepatic cholestasis of pregnancy based on clinical and laboratory indicators.

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
OBJECTIVES: Intrahepatic cholestasis of pregnancy (ICP), a condition exclusive to pregnancy, necessitates prompt identification and intervention to improve the perinatal outcomes. This study aims to develop suitable machine-learning models for predic...

From exencephaly to anencephaly: a catastrophic continuum of neural tube defects from embryogenesis to ultrasonographic diagnosis.

Journal of perinatal medicine
INTRODUCTION: Neural tube defects (NTDs) are severe congenital anomalies arising from incomplete closure of the neural tube during early embryogenesis. Among cranial NTDs, exencephaly, acrania, and anencephaly represent a progressive developmental co...

Fetal neurobehavior and consciousness: a systematic review of 4D ultrasound evidence and ethical challenges.

Journal of perinatal medicine
INTRODUCTION: Recent advancements in four-dimensional (4D) ultrasonography have enabled detailed observation of fetal behavior , including facial movements, limb gestures, and stimulus responses. These developments have prompted renewed inquiry into ...

Comparative reproductive biology, advances in reproductive health, and cultivating inclusion in the scientific community: highlights from the 2024 Annual Meeting of the Society for Reproductive Biology.

Reproduction, fertility, and development
In 2024, the reproductive biology research community in Australia and New Zealand reunited in Adelaide for the Society for Reproductive Biology (SRB) Annual Meeting. The conference showcased major advances made in key areas of reproductive biology, w...

AI in Hypertensive Disorders of Pregnancy: Review.

American journal of hypertension
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are a leading cause of maternal and fetal mortality worldwide. Early detection and risk stratification are critical for timely intervention to prevent severe complications such as eclampsia, strok...

The Maternal Blood Transcriptome Reflects Changes in Fetal Growth and Is an Accurate Predictor of Birth Weight in Cattle.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Harnessing information from maternal blood to predict fetal growth is an emerging area of research in livestock production, offering a noninvasive tool to monitor development. This study aimed to investigate temporal changes in blood gene expression ...

[Assessing the accuracy and comprehensiveness of large language models in responding to patient inquiries on placenta accreta spectrum].

Zhonghua yi xue za zhi
To explore the accuracy and comprehensiveness of responses from four large language models [ChatGPT-3.5 (Model A), ChatGPT-4.0 (Model B), ChatGPT-4o (Model D) developed by OpenAI in the United States, and a domestically developed Obstetric artificia...

Dynamic machine learning models for predicting cesarean delivery risk in women with no prior cesarean delivery: A retrospective nationwide cohort analysis.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To develop and validate advanced machine learning (ML) models for predicting unplanned intrapartum cesarean deliveries in women with no previous cesarean delivery, using both static and dynamic clinical data.

Machine learning approaches for the prediction of retained placenta in dairy cows.

Theriogenology
Retained placenta (RP) is a reproductive disorder that causes significant financial losses to the dairy industry. Predicting RP risk in cows post-calving is a challenging task. This study aimed to evaluate the predictive capabilities of five machine ...