Obstetrics & Gynecology

O-RADS for assessment of adnexal lesions: current status, challenges and future directions.

The Ovarian-Adnexal Reporting and Data System (O-RADS), developed by the American College of Radiology (ACR), provides a standardized, evidence-based framework for risk stratification and management of ovarian and adnexal lesions. The O-RADS system is comprised of two complementary imaging arms: ultrasound (US) and magnetic resonance imaging (MRI). O-RADS US serves as the primary imaging modality ...

MARTP: a multi-agent simulation framework for automated radiation therapy planning based on LLMs.

Objective.High-quality radiotherapy requires accurate dose delivery to target volumes while protecting organs-at-risk. However, current clinical workflows remain constrained by labor-intensive multidisciplinary collaboration, prolonged planning cycles, and limited scalability. Intelligent automation capable of integrating clinical knowledge and real-world decision patterns is needed to enhance pre...

Augmenting Pediatric Care With Artificial Intelligence: Opportunities and Responsibilities for Nurse Practitioners.

BACKGROUND: Artificial intelligence (AI) is emerging as a critical tool for nurse practitioners delivering pediatric and adolescent and young adult (A...

Large Language Models for Breast and Cervical Cancers Communication: Mixed Methods Evaluation Study Assessing Linguistic Quality, Safety, and Accessibility.

BACKGROUND: Effective communication about breast and cervical cancers remains a public health challenge, with widespread misinformation and barriers t...

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. Howev...

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In v...

Near-perfect genome sequencing in medical genetics.

Medical genetics currently operates through a fragmented diagnostic cascade built around short-read sequencing technologies that carry well-documented...

Repurposing Non-oncologic Drugs via Targeted Nanocarriers for Cancer Therapy: Mechanisms, Synergistic Combinations, and Clinical Translation.

The urgent need for innovative cancer therapies has driven increasing interest in repurposing drugs originally developed for non-oncological diseases....

Prenatal Cerium Exposure and Neural Tube Defect Risk: A Case-control Study in Shanxi, China.

Neural tube defects (NTDs) exhibit a multifaceted etiology. Limited research has assessed the association between exposure to metallic and non-metalli...

A two-stage deep learning model with segmentation-guided top-K slice selection for patient-level PAS prediction on MRI.

OBJECTIVE: Placenta accreta spectrum (PAS) can cause severe obstetric complications, and accurate preoperative assessment is critical. However, hetero...

Artificial intelligence-augmented robotic surgery in gynecologic oncology: intraoperative assistance and analytics.

PURPOSE OF REVIEW: Artificial intelligence (AI) is increasingly integrated into robotic-assisted surgery, transforming digital surgical platforms into...

[An auxiliary diagnosis system for cervical intraepithelial neoplasia based on colposcopic images].

Cervical intraepithelial neoplasia is the primary type of cervical precancerous lesion; however, manual clinical diagnosis is prone to bias and has li...

The optimal SVM model from multi-model comparison outperforms conventional criteria in preoperative prediction of ovarian cancer residual disease.

OBJECTIVE: To develop an interpretable artificial intelligence (AI)-based machine learning model integrating 18F-fluorodeoxyglucose positron emission ...

Characterizing the MSMP-CCR2 Interaction through Molecular Dynamics Simulations and Machine Learning Approaches.

The MSMP (MicroSeminoProtein, Prostate-associated) protein is overexpressed in several cancers, including prostate, ovarian, and breast cancers. Its o...

Deep Learning Based on Swin-Transformer and 3D U-Net: Implant Three-Dimensional Position Planning.

INTRODUCTION AND AIMS: This study aimed to devise a deep learning-based model for the automated identification of anatomical mandibular lingual concav...

Deep transfer learning for detection of placenta-mediated diseases from ultrasound images.

Placenta-mediated diseases, such as preeclampsia (PE) and small-for-gestational-age (SGA) neonates, are associated with structural and functional chan...

Bridging the rural logistics penalty: quantifying structural costs and designing policy mechanisms for home TCM delivery to older adults with chronic respiratory diseases.

BACKGROUND: Equitable access to prescribed therapies remains challenging for older adults with chronic respiratory diseases (CRDs) in rural China. Liq...

An Explainable AI Framework for Continuous Monitoring, Risk Stratification, and Clinical Decision Support in Primary Biliary Cholangitis: Protocol for a Multiphase Development and Validation Study.

BACKGROUND: Primary biliary cholangitis (PBC) management remains limited by reliance on static biochemical markers, fragmented assessment of symptom b...

Early risk prediction in endometrial cancer using biomarker and machine learning models: a systematic review and meta-analysis protocol.

BACKGROUND: Globally, endometrial cancer (EC) is among the most prevalent gynaecological cancers, with rising incidence driven by demographic and meta...

Cardiac substructure dosimetry in thoracic radiotherapy: moving beyond mean heart dose and toward precision cardiac risk mitigation.

BACKGROUND: Radiation-induced heart disease (RIHD) remains a clinically significant consequence of thoracic radiotherapy (RT). Historically, the mean ...