Prevention of medical errors

Deep learning-based cervical cancer T-staging using MRI: multi-structure segmentation and classification.

AIMS: Cervical cancer has high incidence and mortality, seriously threatening women's survival and quality of life. Radiologists currently rely mainly on subjective clinical experience for cervical cancer T-staging, which easily leads to misdiagnosis. OBJECTIVES: To develop a deep learning-based technique for automatic segmentation and T-staging of cervical cancer to improve clinical diagnostic ac...

Exosomes in bone health and disease: cellular crosstalk, systemic signaling, and AI-driven advances in regenerative therapy.

Exosomes have emerged as critical mediators of intercellular and inter-organ communication in bone biology. Secreted by bone-resident cells such as osteoblasts, osteoclasts, osteocytes, and mesenchymal stem cells (MSCs), these nanosized vesicles carry diverse molecular cargos that regulate bone remodeling, regeneration, and skeletal homeostasis. In addition to mediating local communication within ...

Identification of senescence-related biomarker for aortic dissection based on bioinformatics and machine learning algorithms.

Aortic dissection (AD) is a vascular surgical disease that seriously threatens human health. Due to a high misdiagnosis rate and unclear pathogenesis,...

Artificial intelligence-enabled digital reproductive health education: corpus-based strategies for strengthening Spanish health communication capacity.

This study examines how corpus-grounded artificial intelligence (AI) can strengthen Spanish reproductive health communication capacity within China's ...

Artificial intelligence driven digital reproductive health education: Building a terminology database to improve Spanish health communication training.

This study proposes an artificial intelligence based pipeline to create a standardized Spanish reproductive health terminology database, addressing ch...

Latent biochemical phenotypes delineate divergent health trajectories in older adults.

Ageing heterogeneity hampers prevention and care. We used routine biochemical panels and unsupervised learning to identify latent phenotypes in commun...

VeNet: a lightweight neural network for efficient brain vessel segmentation in endovascular robotic surgery.

Telesurgery integrates artificial intelligence (AI), robotic systems, sensing technologies, and wireless communication to enable remote and computer-a...

Artificial Intelligence in Hospice and Palliative Care: A Systematic Review of Its Role in Interprofessional Shared Decision-Making Care.

BackgroundArtificial intelligence (AI) is increasingly integrated into hospice and palliative care to support clinical decision-making across clinicia...

Language barriers, mobility, and health equity: clinical risks, economic burden, and policy options for universal language access.

BACKGROUND: International mobility has intensified routine contact between health systems and patients who do not speak the dominant language of care....

Integrating GenAI in a Post-Licensure Pathophysiology Course to Enhance Communication Skills and Promote AI Literacy.

The rapid evolution of Generative Artificial Intelligence (AI) (GenAI) presents new opportunities for enhancing nursing education. This innovation exp...

The VALUE of AI-Guided Communication: Enhancing Shared Decision-Making in Metabolic Bariatric Surgery Consultations Through a Metacognitive Framework.

BACKGROUND: Effective communication in metabolic bariatric surgery (MBS) is essential for patient engagement and adherence, yet surgical residents oft...

A federated learning-enabled energy-aware anomaly detection algorithm for secure big data analytics in IoT-based smart healthcare systems.

The rapid expansion of Internet of Things (IoT) devices in smart healthcare systems has led to the generation of large volumes of diverse medical data...

An exploratory study of the use of artificial intelligence-based virtual patients to enhance dentist-patient communication training.

BACKGROUND: Effective doctor-patient communication is critical in dentistry for diagnostic accuracy and treatment efficacy. Traditional instructional ...

Designing an Artificial Intelligence Transcription Tool to Support Multimodal Serious Illness Communication: Institutional Experience and Best Practices.

BACKGROUND: Communication during serious illness is often complex, emotionally charged, and cognitively demanding, particularly for patients and famil...

Construction of a sports bio mechanical injury prediction and AI warning system based on wearable sensors.

BACKGROUND: Real-time warning and prevention of sports injuries are core challenges in the fields of sports medicine and health management. Traditiona...

What Do We Know About How Generative AI is Being Used for Patient-Centered Communication? A Scoping Review.

This paper offers a scoping review of extant research examining how generative artificial intelligence (AI) is being designed, tested, and used to fac...

Exploring the Use of Artificial Intelligence and Wearable Technologies in the Context of Cardiovascular Prevention From Early Detection to Cardiac Recovery: Protocol for a Scoping Review.

BACKGROUND: Cardiac rehabilitation is an evidence-based, multidisciplinary intervention integrating therapeutic exercise, patient education, nutrition...

Machine learning-assisted validation of a high-isolation THz MIMO antenna for 6G communication and IoT application.

The terahertz (THz) frequency spectrum, which enables ultra-high data rates, low-latency communication (URLLC), and vast connectivity, is poised to be...

Integrative transcriptomic and single-cell analysis reveals metabolic reprogramming and hexosamine biosynthesis-mediated tumor microenvironment remodeling in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common malignancies in men and exhibits substantial clinical heterogeneity. A considerable proportion o...

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfuncti...