AIMC Topic: Pregnancy
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Development and validation of a machine learning model for predicting intrapartum fever using pre-labor analgesia clinical indicators: a multicenter retrospective study.
BMC pregnancy and childbirth
Mar 6, 2025
BACKGROUND: Labor anesthesia is commonly used for pain relief during labor, but it can increase the risk of intrapartum fever. Currently, there are no reliable tools to predict which parturients might develop fever before labor anesthesia. The predic...
Proposing a machine learning-based model for predicting nonreassuring fetal heart.
Scientific reports
Mar 6, 2025
The capacity to forecast nonreassuring fetal heart (NFH) is essential for minimizing perinatal complications; therefore, this research aims to establish if a machine learning (ML) model can predict NFH. This was a retrospective analysis of informatio...
An early prediction model for gestational diabetes mellitus created using machine learning algorithms.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Mar 4, 2025
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...
Prediction of clinical risk factors in pregnancy using optimized neural network scheme.
Placenta
Mar 4, 2025
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...
Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre clinical study.
Scientific reports
Mar 4, 2025
To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional endoanal ultrasound (EAUS). A prospective, comparative, multicentre, international study. Poland, Czec...
Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.
BMC medical informatics and decision making
Mar 3, 2025
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...
Accuracy of machine learning and traditional statistical models in the prediction of postpartum haemorrhage: a systematic review.
BMJ open
Mar 3, 2025
OBJECTIVES: To evaluate whether postpartum haemorrhage (PPH) can be predicted using both machine learning (ML) and traditional statistical models.
Predicting outcomes of expectant and medical management in early pregnancy miscarriage using machine learning to develop and validate multivariable clinical prediction models.
BMC pregnancy and childbirth
Feb 28, 2025
OBJECTIVE: To determine whether readily available patient, ultrasound and treatment outcome data can be used to develop, validate and externally test two machine learning (ML) models for predicting the success of expectant and medical management of m...
Utilization of tree-based machine learning models for predicting low birth weight cases.
BMC pregnancy and childbirth
Feb 26, 2025
BACKGROUND: Low birth weight (LBW) is a health condition that affects over 20 million gestational outcomes worldwide. The current literature indicates that machine learning models have the potential to assist healthcare professionals in predicting LB...
Early gestational diabetes mellitus risk predictor using neural network with NearMiss.
Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology
Feb 24, 2025
BACKGROUND: Gestational diabetes mellitus (GDM) is globally recognized as a significant pregnancy-related condition, contributing to complex complications for both mothers and infants. Traditional glucose tolerance tests lack the ability to identify ...
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