AIMC Topic: Pregnancy Outcome
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Evaluation of Pregnancy Risks in Women with Subchorionic Hematoma Using Machine Learning Models.
Medical science monitor : international medical journal of experimental and clinical research
Dec 21, 2024
BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnancy outcomes. Despite being a relatively common finding in early pregnancy, the effects of SCH on pregnancy outcomes such as miscarriage, stillbirth, a...
Predicting adverse pregnancy outcome in Rwanda using machine learning techniques.
PloS one
Dec 5, 2024
BACKGROUND: Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing to morbidity, mortality, and long-term developmental challenges. This study aimed to predict these outcomes in Rwanda using supervised machine ...
An explainable ultrasound-based machine learning model for predicting reproductive outcomes after frozen embryo transfer.
Reproductive biomedicine online
Nov 28, 2024
RESEARCH QUESTION: Can an optimal machine learning model be developed to predict reproductive outcomes following frozen embryo transfer (FET)?
Improved clinical pregnancy rates in natural frozen-thawed embryo transfer cycles with machine learning ovulation prediction: insights from a retrospective cohort study.
Scientific reports
Nov 27, 2024
This study aims to develop physician support software for determining ovulation time and assess its impact on pregnancy outcomes in natural cycle frozen embryo transfers (NC-FET). To develop, assess, and validate an ovulation prediction model, three ...
IMPACT OF REAL-LIFE ENVIRONMENTAL EXPOSURES ON REPRODUCTION: A contemporary review of machine learning to predict adverse pregnancy outcomes from pharmaceuticals, including DDIs.
Reproduction (Cambridge, England)
Nov 15, 2024
IN BRIEF: Clinical drug trials often do not include pregnant people due to health risks; therefore, many medications have an unknown effect on the developing fetus. Machine learning QSAR models have been used successfully to predict the fetal risk of...
Prediction of clinical pregnancy outcome after single fresh blastocyst transfer during in vitro fertilization: an ensemble learning perspective.
Human fertility (Cambridge, England)
Nov 11, 2024
To establish a predictive model for clinical pregnancy outcomes following the transfer of a single fresh blastocyst in vitro fertilization (IVF). 615 patients (492 in training set and 123 in test set) who underwent the first single and fresh blastocy...
A review of artificial intelligence applications in in vitro fertilization.
Journal of assisted reproduction and genetics
Oct 14, 2024
The field of reproductive medicine has witnessed rapid advancements in artificial intelligence (AI) methods, which have significantly enhanced the efficiency of diagnosing and treating reproductive disorders. The integration of AI algorithms into the...
Predicting newborn birth outcomes with prenatal maternal health features and correlates in the United States: a machine learning approach using archival data.
BMC pregnancy and childbirth
Sep 17, 2024
BACKGROUND: Newborns are shaped by prenatal maternal experiences. These include a pregnant person's physical health, prior pregnancy experiences, emotion regulation, and socially determined health markers. We used a series of machine learning models ...
Can time-lapse culture combined with artificial intelligence improve ongoing pregnancy rates in fresh transfer cycles of single cleavage stage embryos?
Frontiers in endocrinology
Aug 29, 2024
PURPOSE: With the rapid advancement of time-lapse culture and artificial intelligence (AI) technologies for embryo screening, pregnancy rates in assisted reproductive technology (ART) have significantly improved. However, clinical pregnancy rates in ...
Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.
Medicina (Kaunas, Lithuania)
Aug 11, 2024
: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine the predictive performance of four machine learning (ML)-based algorithms for the prediction of adver...
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