Obstetrics & Gynecology

Evaluating the usability and practicality of AI-enabled smartphone-based obstetric ultrasound in Sierra Leone: a mixed-methods study.

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apoptotic cell death and senescence pathways contribute to tumor evolution and immunosuppression, their integration into predictive models for multi-target drug design and immunotherapy optimization is underexplored. Machine learning was used to identify k...

Reinventing miRNA cancer therapy through immunomodulation and AI.

Despite the rational therapeutic premise of microRNA (miRNA) replacement or inhibition for cancer treatment, its clinical translation remains signific...

From structural complexity to causal representation: A dynamic fractal-attention framework for fine-grained ovarian tumor classification in ultrasound.

Accurate fine-grained classification of ovarian tumors from ultrasound images remains challenging due to speckle noise, boundary ambiguity, structural...

Artificial Intelligence in Minimally Invasive Gynecological Surgery: A Systematic Review of Task- Specific Performance and Clinical Translational Readiness.

OBJECTIVE: To systematically evaluate the task-specific performance and clinical translational readiness of artificial intelligence (AI) applications ...

Predicting cervical cancer among women living with HIV/AIDS at public health facilities in a resource-limited setting in Ethiopia using machine learning analysis.

Comparison of multistage and single-stage framework for automated landmark localization and radiologic measurement: a case of the C1-2 complex on cervical spine lateral radiographs.

Machine learning based classification in obstetrics: evaluating models, partitioning strategies, and key predictors in cardiotocography.

Prediction of retained placenta in holstein dairy cows based on machine learning approaches: Comparative analysis of risk factors and predictive algorithms.

Retained placenta (RP) is a common postpartum disorder in dairy cows that significantly impairs reproductive performance and farm profitability. This ...

Optimizing Timeliness of Healthcare Delivery in Diagnostic Radiology at U.S. Academic Centers.

RATIONALE AND OBJECTIVES: Timely radiology access is essential for accurate diagnosis, treatment planning, and efficient care delivery. U.S. academic ...

Development trends and translational opportunities in self-assembled herbal bioactive materials research.

BACKGROUND: Self-assembled herbal bioactive materials (SAHBMs) represent a rapidly advancing frontier integrating phytochemistry, supramolecular chemi...

Fetal Fraction and Uterine Leiomyoma Volume: New Insights From Interpretable Modeling.

OBJECTIVE: This study aims to develop a predictive model to estimate the likelihood of achieving a sufficient fetal fraction (FF) for non-invasive pre...

Image analysis for cervical cancer classification using deep learning techniques.

Engineering brain-penetrant PROTACs: Bridging molecular design and CNS delivery.

The drug development for central nervous system (CNS) disorders, particularly neurodegenerative diseases, such as Alzheimer's disease, Parkinson's dis...

Artificial intelligence-assisted design and optimization of stimuli-responsive nanocarriers for smart drug delivery.

Stimuli-responsive nanostructures are a revolutionary breakthrough in the controlled delivery of drugs, allowing for their precise spatiotemporal cont...

Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies.

BACKGROUND: The infection of high-risk human papillomavirus (hr-HPV) and related cervical cancer have greatly threatened women's health. However, the ...

Fusing imaging and metabolic modeling via multimodal deep learning in ovarian cancer.

Integrating genotype (e.g., transcriptomics), phenotype (e.g., imaging), and tumor microenvironment (e.g., metabolomics) is crucial to elucidating the...

Computational identification of diagnostic biomarkers linking Dibutyl phthalate exposure to ovarian cancer through network toxicology and machine learning.

A deep dive into ferritin nanoparticle advancements: experimental and computational perspectives.

Ferritin, a natural iron-storage protein, has emerged as a versatile platform in nanotechnology and biomedicine due to its biocompatible 12 nm nanocag...

Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.

Radiotherapy (RT) remains a cornerstone of cancer management but is fundamentally constrained by normal tissue toxicity, intrinsic and acquired radior...