Obstetrics & Gynecology

The Future of Parenthood? Examining the Promise and Complexity of Pregnancy Robots in Reproductive Health.

Advancements in reproductive technology are now approaching an unprecedented frontier: the pregnancy robot, a potential artificial womb capable of carrying a fetus from fertilization to birth. This innovation, by simulating the natural uterine environment, could redefine pregnancy and parenthood, offering transformative benefits for maternal and infant health. The pregnancy robot promises safer pa...

'Applications of machine learning in liposomal formulation and development'.

Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly in the design and optimization of liposomal formulations. This review focuses on the intersection of ML and liposomal technology, highlighting how advanced algorithms are accelerating formulation processes, predicting key parameters, and enabling personalized therapies. ML-driven approaches are restructuring ...

Integrative machine learning frameworks to uncover specific protein signature in neuroendocrine cervical carcinoma.

OBJECTIVE: Neuroendocrine cervical carcinoma (NECC) is a rare but highly aggressive tumor. The clinical management of NECC follows neuroendocrine neop...

Deep Learning-Based Segmentation of Cervical Posterior Longitudinal Ligament Ossification in Computed Tomography Images and Assessment of Spinal Cord Compression: A Two-Center Study.

OBJECTIVE: This study aims to develop a fully automated, computed tomography (CT)-based deep learning (DL) model to segment ossified lesions of the po...

Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.

Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluati...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to enhance drug efficacy and reduce toxicity through ...

Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machine learning study.

BACKGROUND: Predictive, preventive, and personalized medicine (PPPM/3PM) is a strategy aimed at improving the prognosis of cancer, and programmed cell...

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

Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge th...

Enhancing repeatability of follicle counting with deep learning reconstruction high-resolution MRI in PCOS patients.

Follicle count, a pivotal metric in the adjunct diagnosis of polycystic ovary syndrome (PCOS), is often underestimated when assessed via transvaginal ...

Screening of serum biomarkers in patients with PCOS through lipid omics and ensemble machine learning.

Polycystic ovary syndrome (PCOS) is a primary endocrine disorder affecting premenopausal women involving metabolic dysregulation. We aimed to screen s...

A bird's-eye view of the biological mechanism and machine learning prediction approaches for cell-penetrating peptides.

Cell-penetrating peptides (CPPs) are highly effective at passing through eukaryotic membranes with various cargo molecules, like drugs, proteins, nucl...

A randomized sequential allocation study on the optimum programmed intermittent epidural boluses interval time with different concentrations of ropivacaine combined with the dural puncture epidural technique for labor analgesia.

BACKGROUND: The combined technique of programmed intermittent epidural boluses (PIEB) and dural puncture epidural (DPE) is currently considered a more...

The role of artificial intelligence in gynecologic and obstetric emergencies.

OBJECTIVE: To investigate the potential of artificial intelligence (AI) in emergency medicine, focusing on its utility in triaging and managing acute ...

Beyond the hot flashes: how machine learning is uncovering the complexity of menopause-related depression.

BACKGROUND: The transition into menopause marks a significant stage in a woman's life, indicating the end of reproductive capability. This period, enc...

Development and validation of a support vector machine-based nomogram for diagnosis of obstetric antiphospholipid syndrome.

BACKGROUND: Antiphospholipid Syndrome (APS) is a systemic autoimmune disorder characterized by arterial or venous thrombosis and/or pregnancy complica...

Neural Network and Logistic Regression Models Based on Ultrasound Radiomics and Clinical-Pathological Features to Predict Occult Level II Lymph Node Metastasis in Papillary Thyroid Carcinoma.

RATIONALE AND OBJECTIVES: Papillary thyroid carcinoma (PTC) often metastasizes to lateral cervical lymph nodes, especially in level II. This study aim...

AI-based processing of future prepared foods: Progress and prospects.

The prepared foods sector has grown rapidly in recent years, driven by the fast pace of modern living and increasing consumer demand for convenience. ...

Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.

Predicting disease-related molecular traits from histomorphology brings great opportunities for precision medicine. Despite the rich information prese...

Development of machine learning models for diagnostic biomarker identification and immune cell infiltration analysis in PCOS.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age. It is characterized by symptoms such ...

A novel non-invasive murine model for rapidly testing drug activity via inhalation administration against .

The efficacy of many compounds against is often limited when administered via conventional oral or injection routes due to suboptimal pharmacokinetic...