Clinical Trials

Vaccination attitudes and intentions reported by Canadian children and their parents in the CHILD Cohort Study during the COVID-19 pandemic.

BACKGROUND: Understanding if and how vaccination attitudes are shared among family members can help inform strategies to increase uptake. We assessed the correlation of self-reported COVID-19 vaccination attitudes and uptake among Canadian children and their parents, and investigated predictors of parents' attitudes in January 2021-2022. METHODS: We studied a subset of 1458 CHILD Cohort Study hous...

Artificial intelligence in population-based cancer screening: evidence from a national survey of Italian professionals.

BACKGROUND: Artificial Intelligence (AI) is increasingly proposed to enhance population-based cancer screening. While several applications are under evaluation, there is limited evidence on professional and organisational perspectives regarding their value, risks, and implementation challenges. METHODS: We conducted a web-based survey targeting coordinators and reference professionals of Italian c...

Next generation risk assessment and new approach methodologies for sustainable management of heavy metal contaminated environments: A critical review.

Environmental stability forms the foundation for sustaining healthy ecosystems and protecting human life, but the relentless accumulation of persisten...

Enabling Drug-Drug Interaction Event Prediction with Multi-view-enhanced Chemical Structural Information.

Predicting drug-drug interaction (DDI) events is critical for ensuring patient safety, optimizing therapeutic efficacy, and advancing drug discovery. ...

Coconstructing CHAMP, an Artificial Intelligence Chatbot for Pediatric Infectious Symptoms Management: Protocol for a Multiphase Participatory Study.

BACKGROUND: Acute infectious symptoms are a leading cause of pediatric emergency department visits in Canada, many of which are low acuity and could b...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophancy, and AI-as...

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...

Staffing, workflow, and operational models in virtual nursing and remote safety observation: A scoping review.

BACKGROUND: Virtual nursing and remote safety observation have emerged as critical nurse-led workforce innovations, yet standardized evidence on staff...

Navigating the regulatory landscape of herbal medicines: A global comparison of India, China, Europe, the United States and Japan.

The use of herbal medicines is expanding rapidly worldwide, but regional regulatory systems vary greatly, leading to variations in quality, safety and...

Differences in Safety Risks Across Languages in Health-Relevant Queries: Vulnerability Analysis of Large Language Model Responses.

BACKGROUND: Large language models (LLMs) such as ChatGPT are increasingly used to support health-related queries and decision-making. However, these m...

Multicentre prospective cohort study to develop and validate a machine learning-based model for predicting 6-month all-cause mortality in elderly patients with advanced chronic obstructive pulmonary disease in China: study protocol.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality predicti...

Global evolution of robot-assisted cholecystectomy research in the era of artificial intelligence: a bibliometric and knowledge-mapping study.

OBJECTIVE: To systematically map the global evolution, collaborative networks, knowledge structure, and emerging research hotspots in robot-assisted c...

Feasibility and challenges of large language model (LLM)-generated neonatal resuscitation simulations: a multicenter exploratory study.

BACKGROUND: Simulation-based training (SBT) in neonatal resuscitation has positive impact on educational and neonatal outcomes. However, the implement...

A machine learning and physics-informed framework for predictive modeling of gemcitabine nanocomposite cytotoxicity.

BACKGROUND: Gemcitabine is an important chemotherapeutic agent that suffers from poor bioavailability and drug resistance. Although the nanocomposite ...

Overcoming LPS-mediated resistance in gram-negative pathogens: a review of LL-37 analogs and computational design strategies.

The increasing incidence of antimicrobial resistance (AMR) in Gram-negative bacteria has become a significant global health issue, driven primarily by...

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...

Machine learning model-guided selective use of temporary diverting ileostomy in rectal cancer surgery: a randomized controlled trial.

The appropriate use of temporary diverting ileostomy (TDI) in rectal cancer surgery lacks standardized criteria. A randomized controlled trial was per...

A multi-domain graph-integrated neural framework for robust acoustic anomaly detection under adverse environmental conditions.

Acoustic event understanding and anomaly detection play a critical role in security monitoring, defence applications, and urban safety, yet current ap...

Comparative evaluation of information quality, readability, and guideline consistency of large language model-generated educational content on hemodialysis complications: a cross-sectional assessment of generative AI-driven chatbots.

BACKGROUND: Large language models are increasingly becoming a key resource for hemodialysis patients to access information on disease management. Howe...

Predicting fire consequences with the transformer model based on multimodal feature fusion.

Accurate prediction of fire consequences is fundamental to process safety management and quantitative risk assessment in the chemical process industri...