Obstetrics & Gynecology

Hierarchical machine learning models for predicting antenatal care utilisation among Nigerian women: Identifying actionable insights for health policy.

Harnessing lipid-driven immunometabolic pathways in omental metastases to enhance immunotherapy in patients with ovarian cancer.

Immunotherapy with immune checkpoint blockade (ICB) in epithelial ovarian carcinoma (EOC) shows limi...

A deep-learning-based early warning system for abnormal eye conditions in chickens.

In current poultry production practice, farmers are required to frequently enter their poultry house...

Performance of next-generation AI chatbots in gynecological knowledge assessment: a comparative pilot study of ChatGPT-5, Gemini-3, DeepSeek-V3.2, and Claude-4.5-Opus.

PURPOSE: As artificial intelligence (AI) models evolve into their next generations, their applicatio...

Artificial Intelligence Integration in Radiation Therapy Education: A Multi-Modal Approach.

INTRODUCTION: Critical workforce shortages in radiation oncology have led tertiary institutions to r...

Minimally invasive surgery for advanced-stage ovarian cancer: a review of evidence and emerging paradigms.

Minimally invasive surgery has emerged as a promising approach to the management of advanced-stage e...

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress ...

Redefining Cytotechnologist Practice in Sweden: National Survey on Workload, Expanded Roles, and Future Competency Needs.

INTRODUCTION: Cytotechnologists have long been central to cervical cancer screening, although their ...

Deep learning-based labor relations prediction system with multi-source data fusion and early warning mechanisms.

Predicting workplace conflicts before they escalate into formal disputes or collective action repres...

Nano-antimicrobial peptides (Nano-AMPs) to combat resistant gram-negative bacteria.

The emergence of antimicrobial resistance (AMR) poses a critical threat to public health worldwide, ...

Machine learning-based integration of antiphospholipid antibodies for predicting pregnancy outcomes in patients with recurrent spontaneous abortion: a multicenter prospective study.

OBJECTIVES: Antiphospholipid antibodies (aPLs) are closely associated with recurrent spontaneous abo...

Sustainable Strategies in Tuberculosis Management: Bridging Ethnobotanical Pharmacology, Advanced Drug Delivery, and AI-Driven Innovation.

Tuberculosis (TB) persists as a leading infectious disease, with progress in global control complica...

Transformer-based multidimensional feature fusion for accurate prediction of lipid nanoparticles transfection efficiency.

RNA-based technologies have demonstrated significant potential for diverse applications, ranging fro...

Evaluation of the Effectiveness of an AI-assisted, Dual-Template Workflow in Improving the Accuracy of Tooth Autotransplantation.

OBJECTIVE: To test whether an AI-assisted, dual-template workflow improves plan-delivery accuracy in...

Exosome-enabled bone defect repair: mechanistic foundations, bioengineered delivery, and artificial intelligence-driven translation.

Bone defects remain a substantial clinical burden. Exosomes have been extensively investigated as ce...

Advanced Drug Delivery Strategies for Overcoming Biological Barriers: Tumor Microenvironment and Blood-Brain Barrier.

Therapeutic efficacy for malignancies and neurological disorders is fundamentally restricted by biol...

Versatile Backdoor Attack With Visible, Semantic, Sample-Specific and Compatible Triggers.

Deep neural networks (DNNs) can be manipulated to exhibit specific behaviors when exposed to specifi...

Leveraging artificial intelligence to decipher gynecologic cytopathology reports: Insights from an exploratory study for possible use in patient portals.

BACKGROUND: The 21st Century Cures Act allows patients to have immediate access to their medical rec...

Evaluating Performance of a Deep Learning-based Artificial Intelligence Model for Ovarian Tumor Classification Using a Multicenter CT Dataset.

Purpose To develop a deep learning-based, computer-aided diagnosis (CADx) model for preoperative cla...

Modeling Polymeric Drug Release: The Emerging Role of Machine Learning.

Polymeric drug formulations have significantly improved the safety, efficacy, and clinical impact of...

Human and artificial intelligence performance in radiographic caries detection: ex vivo tooth section-referenced evaluation and implications for clinical decision-making.

OBJECTIVES: To evaluate the caries detection performance of a commercially available AI-system (Nost...