Surveillance

An open-access fire detection image dataset for research in computer vision and safety monitoring.

This article presents the Fire Recognition Image Dataset, a comprehensive collection of images designed to support research in fire detection, smoke recognition, and safety monitoring using computer vision techniques. The dataset was created by systematically selecting publicly available YouTube videos depicting both fire and non-fire scenarios. Sources included uncontrolled fires such as forest, ...

Reporting software tools and automation in the protocols of evidence syntheses: Meta-research study.

INTRODUCTION: The growing volume of primary research and the increasing demand for timely, high-quality evidence syntheses (ESs) have intensified interest in using software, automation, and artificial intelligence. While guidance such as PRISMA 2020 encourages reporting automation in completed ESs, there is little emphasis on documenting planned automation at the protocol stage. This gap is critic...

Artificial Intelligence in Colonoscopy Surveillance for Lynch Syndrome: Emerging Evidence, Lessons Learned From Average-Risk Populations, and Future Directions.

Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome and is characterized by an accelerated adenoma-carcinoma sequence, ...

Nurses' Lived Experiences of Generative Artificial Intelligence-Enabled Shift Handover Innovation: A Descriptive Phenomenological Study.

AIM: To explore nurses' lived experiences of a generative artificial intelligence-enabled shift handover innovation. DESIGN: A descriptive phenomenolo...

Exploring Attitudes Toward AI-Based Contactless Sensors in Health Among Five Stakeholder Groups: Qualitative Study.

BACKGROUND: The rapid rise of artificial intelligence-based contactless sensors (AI-CS) is expected to significantly transform how patients are measur...

Influenza forecasting method based on dual-chan nel feature fusion of VMD decomposition.

Accurate influenza forecasting is critical for timely public health responses and resource allocation. To address challenges such as strong non-statio...

Methodological appraisal practices in AI-Based radiomics research in paediatric brain tumour Imaging: A Meta-Research study of systematic reviews.

BACKGROUND: Artificial intelligence-based radiomics offers a potential adjunct to the current clinical management of paediatric brain tumours by enabl...

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 ...

Segmentation for pelvic malignancies in radiation oncology practice: a systematic review and meta-analysis protocol.

BACKGROUND: Deep learning (DL)-based artificial intelligence (AI) models, the fourth generation in autosegmentation, have been adopted both for commer...

Using tree-based ensemble methods to produce a population-based mortality risk score in Ontario, Canada.

INTRODUCTION: Risk adjustment is critical in observational epidemiology to control for confounding of the exposure-outcome relationship. Accurate pred...

Variation in standards for reporting artificial intelligence research using burn image datasets raises ethical questions: A scoping review.

BACKGROUND: Accurate assessment of burn depth and area are required to guide treatment and inform prognosis. Currently this assessment relies on subje...

Artificial intelligence and machine learning: an important new set of tools for clinical shoulder arthroplasty research.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have increasingly transformative potential in orthopedic surgery, enhancing precisi...

Monitoring airline pilot mental health: a 3PM framework utilising digital phenotyping and AI.

The aeromedical certification of commercial airline pilots relies on periodic, self-disclosure-dependent assessments. However, this reactive model lac...

AI Triage of Normal Chest Radiographs: A Silent Trial and Failure Analysis.

Chest radiography is the most frequently performed imaging examination worldwide, and increasing demand has contributed to reporting delays in many he...

Comparative evaluation of large language models for generating CAD-RADS 2.0-compliant diagnostic conclusions in cardiac CT reports.

OBJECTIVES: Coronary computed tomography angiography (CCTA) has become a cornerstone in non-invasive CAD diagnosis and risk stratification. To standar...

Integrating theory and machine learning to reveal determinants of plasmid copy number.

Plasmids are extrachromosomal mobile genetic elements whose copy numbers (PCNs) critically influence microbial evolution, antibiotic resistance and pa...

Centralized pooling and federated learning for Canadian patient-level data sharing in multicenter medical AI: A scoping review.

Algorithms that support screening, triage, and treatment decisions depend on training data drawn from patient populations. Limited access to patient-l...

Decoding viral evolution through integrative bioinformatics: From genomes to global health.

Bioinformatics has transformed modern virology by linking genomic variation to epidemiology, protein structure, and public health action. This review ...

Online surveys, a breakthrough in research, especially in nutrition and food sciences.

BACKGROUND: Technological advancements and widespread internet connectivity have fundamentally transformed data collection across academic disciplines...

From risk to resilience: A narrative review on strengthening veterinary clinical biosecurity to prevent healthcare-associated infections.

Veterinary clinical biosecurity is key to preventing infectious diseases in animal clinics, particularly when there is high patient turnover, a mix of...