AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Labor, Induced

Showing 1 to 10 of 11 articles

Clear Filters

Tafoxiparin, a novel drug candidate for cervical ripening and labor augmentation: results from 2 randomized, placebo-controlled studies.

American journal of obstetrics and gynecology
BACKGROUND: Slow progression of labor is a common obstetrical problem with multiple associated complications. Tafoxiparin is a depolymerized form of heparin with a molecular structure that eliminates the anticoagulant effects of heparin. We report on...

A Dynamic Compliance Cervix Phantom Robot for Latent Labor Simulation.

Soft robotics
Physical simulation systems are commonly used in training of midwifery and obstetrics students, but none of these systems offers a dynamic compliance aspect that would make them more truly representative of cervix ripening. In this study, we introduc...

A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting.

Biometrical journal. Biometrische Zeitschrift
Propensity score matching (PSM) and propensity score weighting (PSW) are popular tools to estimate causal effects in observational studies. We address two open issues: how to estimate propensity scores and assess covariate balance. Using simulations,...

Quantifying the Impacts of Pre- and Post-Conception TSH Levels on Birth Outcomes: An Examination of Different Machine Learning Models.

Frontiers in endocrinology
BACKGROUND: While previous studies identified risk factors for diverse pregnancy outcomes, traditional statistical methods had limited ability to quantify their impacts on birth outcomes precisely. We aimed to use a novel approach that applied differ...

Prediction of low Apgar score at five minutes following labor induction intervention in vaginal deliveries: machine learning approach for imbalanced data at a tertiary hospital in North Tanzania.

BMC pregnancy and childbirth
BACKGROUND: Prediction of low Apgar score for vaginal deliveries following labor induction intervention is critical for improving neonatal health outcomes. We set out to investigate important attributes and train popular machine learning (ML) algorit...

Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.

Scientific reports
To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. The subjects were divided into primipara and multipara, and the risk factors for the outcomes of indu...

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...

Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: Induction of labor, often used for pregnancy termination, has globally rising rates, especially in high-income countries where pregnant women present with more comorbidities. Consequently, concerns on a potential rise in cesarean sectio...