Infertility

Next-generation Approaches in Targeting Polycystic Ovarian Syndrome: Innovative Strategies.

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder that affects millions of women worldwide and is characterized by ovarian dysfunction, hyperandrogenism, and metabolic abnormalities. The traditional diagnostic and therapeutic approaches often fail to address the multifaceted nature of PCOS. Recent advancements in next-generation sequencing (NGS), bioinformatics, and precision medici...

High throughput recurrent pregnancy loss screening: urine metabolic fingerprints LDI-MS and machine learning.

Infertility is a significant challenge faced by many families worldwide, with recurrent pregnancy loss (RPL) being a prevalent cause of infertility among women. This condition causes immense emotional and physical distress for affected individuals and their families. In this study, we present a rapid, efficient, and high-throughput analytical method using PS@FeO-NH magnetic beads as a matrix for t...

Exploration of immune-related diagnostic biomarkers in unexplained infertility by bioinformatics analysis and machine learning.

OBJECTIVE: We aimed to discover the biomarkers associated with UI and their correlation with immune cell infiltration.

Graph Network for Sign Language Tasks

Recent advances in sign language research have benefited from CNN-based backbones, which are primarily transferred from traditional computer vision ...

The Impact of Model Zoo Size and Composition on Weight Space Learning

Re-using trained neural network models is a common strategy to reduce training cost and transfer knowledge. Weight space learning - using the weight...

Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early le...

Artificial intelligence in assisted reproductive technology: separating the dream from reality.

This paper critically reviews the role of artificial intelligence (AI) in assisted reproductive technology (ART), a nascent field that has emerged ove...

Evaluating the Feasibility and Accuracy of Large Language Models for Medical History-Taking in Obstetrics and Gynecology

Effective physician-patient communications in pre-diagnostic environments, and most specifically in complex and sensitive medical areas such as infe...

Artificial intelligence-based tissue segmentation and cell identification in multiplex-stained histological endometriosis sections.

STUDY QUESTION: How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue comp...

Artificial intelligence-driven analysis of embryo morphokinetics in singleton, twin, and triplet pregnancies.

In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one...

An Automated Machine Learning Framework for Surgical Suturing Action Detection under Class Imbalance

In laparoscopy surgical training and evaluation, real-time detection of surgical actions with interpretable outputs is crucial for automated and rea...

ILETIA: An AI-enhanced method for individualized trigger-oocyte pickup interval estimation of progestin-primed ovarian stimulation protocol

In vitro fertilization-embryo transfer (IVF-ET) stands as one of the most prevalent treatments for infertility. During an IVF-ET cycle, the time int...

DeFusion: An Effective Decoupling Fusion Network for Multi-Modal Pregnancy Prediction

Temporal embryo images and parental fertility table indicators are both valuable for pregnancy prediction in \textbf{in vitro fertilization embryo t...

Marker-independent imaging reveals a correlation of fibrotic and epigenetic alterations in endometriosis

Endometriosis describes the presence of endometrial glands outside of the uterus and can cause various symptoms such as chronic pelvic pain, hypermeno...

Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological...

Label-free 3D subcellular phenotyping of mouse embryos by holotomography enables early prediction of blastocyst formation

Accurate embryo quality assessment is central to improving outcomes in in vitro fertilization (IVF), yet current practice relies mainly on subjective ...

Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis

Endometriosis affects ∼10% of reproductive-age women, yet targeted non-hormonal therapies remain unavailable, and treatment response is highly variabl...

Phenotyping Adolescent Endometriosis: Characterizing Symptom Heterogeneity Through Note- and Patient-Level Clustering

Pelvic pain (dysmenorrhea and non-menstrual) is the most common presentation of adolescent endometriosis, but symptoms vary between and within patient...

AI-Driven Fluorescence Peak Analysis for Chromosomal Aneuploidy Detection: A Python-Based Machine Learning Approach for Enhanced Accuracy and Efficiency

Chromosomal aneuploidy, a condition characterized by an abnormal number of chromosomes, is a major genetic disorder affecting human reproduction, lead...

Predicting Bacterial Vaginosis Development using Artificial Neural Networks

Bacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterized by the depletion of protective Lactobacillus spp. and overgrowth of a...