Hospital-Based Medicine

From Earthly companions to extraterrestrial countermeasures: rethinking AI-mediated intimacy for long-duration spaceflight through modular autonomous intimacy companion architecture.

The prospect of multi-year missions to the Moon and Mars raises unresolved questions about intimacy, attachment, loneliness and sexual expression in isolated, confined and increasingly autonomous habitats. While the physiological, psychological and operational risks of spaceflight have been extensively studied, sexual intimacy remains a taboo domain, leaving little policy, design guidance or behav...

Deep learning‑based ultra-high-resolution CT imaging of viral pneumonia at admission and after discharge.

The relationship between artificial intelligence literacy and artificial intelligence anxiety: A cross-sectional study among pediatric nurses.

AIM: This study aimed to investigate the relationship between pediatric nurses' levels of artificial intelligence literacy and artificial intelligence...

Physiology-informed machine learning for patient-level surgical decision-making in severe traumatic brain injury: Multicenter model development with external validation.

BACKGROUND: Surgical decisions for severe traumatic brain injury (TBI) are often made under prognostic uncertainty. Existing prognostic models predict...

Exploring novel kinetics of automated H2O2 nebulization: a breakthrough in SARS-CoV-2 elimination.

Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in healthcare settings, its precise kinetics and real-w...

Artificial intelligence for nursing data visibility in health technology assessment: policy architecture and implementation considerations.

Background: Health technology assessment (HTA) increasingly informs reimbursement, adoption, scale-up, and disinvestment decisions, yet many evidentia...

Periprocedural evaluation of patients with BAV stenosis undergoing TAVR: a machine learning-based study.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for patients with severe bicuspid ...

Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study.

OBJECTIVES: To develop and evaluate an explainable machine learning framework enhanced with synthetic data generation to predict unplanned 30-day hosp...

Underperformance of Machine Learning Models Predicting Readmission and Prolonged Length of Stay Following Total Knee Arthroplasty Among Underrepresented Populations: Fairness Analysis and Mitigation Strategies.

BACKGROUND: While machine learning (ML) models demonstrate high predictive accuracy, recent studies reveal that ML models underperform for smaller sub...

Progress of Multimodal Imaging: Bridging Orthodontics to Comprehensive Oral Multidisciplinary Care.

INTRODUCTION AND AIMS: For decades, orthodontic diagnosis and treatment have primarily depended on physical models, imaging techniques, and three-dime...

Predicting one-year mortality risk in ICU patients with ischemic stroke using multi-algorithm machine learning and a nomogram.

Introduction: Ischemic stroke is a leading cause of mortality, and patients requiring intensive care unit (ICU) admission carry a guarded prognosis. W...

An Intelligent Interactive Management Platform for Rheumatoid Arthritis Care: Real-World Observational Study.

BACKGROUND: Effective postdischarge management is essential for maintaining disease control and improving long-term outcomes in rheumatoid arthritis (...

Current Patient Attitudes to Artificial Intelligence Applications in Radiology.

OBJECTIVES: Healthcare systems are now funding implementation of artificial intelligence (AI) algorithms in radiology, which will change the experienc...

Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.

BACKGROUND: People with stroke face a high mortality risk, and an accurate prediction model is essential to the guidance of clinical decision-making i...

Analyzing multiple-sclerosis progression: stage-specific biomarker insights via explainable machine learning.

BACKGROUND: Multiple Sclerosis (MS) is a chronic autoimmune disease where early diagnosis from Clinically Isolated Syndrome (CIS) remains challenging....

Parsimonious and explainable biomarker-based severity score for hospitalised patients with COVID-19-related respiratory infections: development, validation and XAI benchmarking.

BACKGROUND: Severity scoring systems are increasingly important tools for stratifying hospitalised patients, guiding treatment decisions, and enabling...

An inventory of emergency department information systems (EDIS) in Canada: Benchmarking system functionality and technology readiness.

OBJECTIVES: Emergency Department Information Systems (EDIS) are essential digital technology used in Emergency Departments (ED). Modern EDIS provide e...

Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.

There is growing interest in understanding how generative artificial intelligence (GenAI) can support patients and caregivers in making informed healt...

Sustainable methylene blue dye removal via bio-derived micro/micron-sized porous particles Zygophyllum coccineum and Calotropis procera: A machine learning-assisted study.

UNLABELLED: The discharge of synthetic dyes into aquatic ecosystems poses a critical threat to environmental and human health, necessitating urgent, c...

Deep learning model for pathological invasiveness prediction using smartphone-based surgical resection images in clinical stage IA lung adenocarcinoma (SuRImage): a prospective, multicentric, diagnostic study.

BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segme...