AIMC Topic: Progesterone

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Machine learning-based preliminary screening tool for clinical pregnancy prediction: towards management of IVF/ICSI stages.

Annals of medicine
BACKGROUND: Accurate prediction of pregnancy outcomes in assisted reproductive technology (ART) remains a clinical challenge due to the complexity and heterogeneity of IVF/ICSI cycles. Existing models often focus on isolated treatment stages and rely...

Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment III Trial Revisited: Objective Classification of Traumatic Brain Injury With Brain Imaging Segmentation and Biomarker Levels.

Critical care explorations
OBJECTIVE: This post hoc study of the Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment (ProTECT) III trial investigates whether improving traumatic brain injury (TBI) classification, using serum biomarkers (glial fibrillary ac...

Explainable artificial intelligence to identify follicles that optimize clinical outcomes during assisted conception.

Nature communications
Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple 'ru...

Preovulatory progesterone levels are the top indicator for ovulation prediction based on machine learning model evaluation: a retrospective study.

Journal of ovarian research
BACKGROUND: Accurately predicting ovulation timing is critical for women undergoing natural cycle-frozen embryo transfer. However, the precise predicting of the ovulation timing remains challenging due to the lack of consensus among different clinics...

Effects of exogenous energy on synthesis of steroid hormones and expression characteristics of the CREB/StAR signaling pathway in theca cells of laying hen.

Poultry science
Energy and the cAMP-response element binding protein (CREB)/steroidogenic acute regulatory protein (StAR) signaling pathway play important roles in steroid hormone production and follicular development in hens. This present study aimed to investigate...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

Frontiers in endocrinology
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...

Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...

Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images.

Scientific reports
Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorith...

Secretion of equine chorionic gonadotropin and its association with supplementary corpus luteum formation and progesterone concentration in Hokkaido native pony recipient mares.

Domestic animal endocrinology
The objectives of this study were to determine the plasma profile of equine chorionic gonadotropin (eCG) and its association with the formation of supplementary corpus luteum (CL) and plasma progesterone concentrations in embryo transfer Hokkaido nat...