Surveillance

Incorporating artificial intelligence into imaging for surveillance and diagnosis of liver cancer: Innovations, challenges, and clinical translation.

Primary liver cancer, mainly hepatocellular carcinoma and intrahepatic cholangiocarcinoma, remains a leading cause of cancer mortality worldwide. Early detection is crucial for curative treatment, yet current surveillance and diagnostic strategies, primarily ultrasound surveillance and contrast-enhanced CT or MRI, suffer from operator dependence, limited sensitivity, and interpretive variability. ...

Artificial Intelligence-Based Medical Devices for Diabetic Retinopathy Screening in the European Union.

BACKGROUND: Diabetic retinopathy (DR) remains a leading cause of preventable blindness, yet screening programs across Europe face persistent workforce and capacity constraints amid rising diabetes prevalence. Artificial intelligence (AI)-enabled screening platforms have been developed to support scalable DR detection; however, their regulatory status, validation approaches, and implementation read...

Predicting antimicrobial resistance in Staphylococcus aureus using machine learning: Insights from a five-year surveillance study.

Staphylococcus aureus is a leading cause of both community- and hospital-acquired infections, and the growing prevalence of antimicrobial resistance c...

Pathology of peripheral neuroblastic tumors.

Neuroblastoma is the most prevalent extracranial solid tumor in pediatric age populations worldwide and the most common neoplastic disease diagnosed i...

Characterization of Models for Identifying Physical and Cognitive Frailty in Older Adults With Diabetes: Systematic Review and Meta-Analysis.

BACKGROUND: Physical frailty and cognitive frailty are increasingly recognized as critical geriatric syndromes among older adults with diabetes, contr...

Detection of Antithrombotic-Related Bleeding in Older Inpatients: Multicenter Retrospective Study Using Structured and Unstructured Electronic Health Record Data.

BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrom...

Interepidemic Rift Valley fever in East Africa: the recent risk landscape and projected impacts of global change.

Rift Valley fever (RVF) is a zoonotic disease that causes sporadic, multi-country epidemics. However, there is limited understanding of RVF virus circ...

Interdisciplinary expertise to advance human-centered explainable AI.

The field of artificial intelligence (AI) is rapidly influencing health and healthcare, but bias and inadequate subgroup performance persists. Previou...

Integrating artificial intelligence (AI) into colorectal cancer reporting.

Artificial intelligence (AI) and deep learning (DL) are transforming cancer research and clinical care, with histopathology playing a central role in ...

Machine Learning forecasting of dengue in São Paulo using virtual data augmentation and urban incident predictors: Addressing the exceptional surge of cases in 2024.

Dengue remains one of the most critical vector-borne diseases globally, with Brazil consistently reporting the highest incidence in the Americas. The ...

Beyond Residential Ambient Concentrations: Quantifying Exposure Error and Advancing Personal PM2.5 Prediction with a Scalable Modeling Framework.

Accurate assessment of personal PM2.5 exposure is essential but challenging in large-scale epidemiology, as conventional residential ambient data ofte...

The OnSPARK LTC Data Platform: Leveraging interRAI to Build a Learning Health System for Long-Term Care.

Long-Term Care (LTC) in Canada faces persistent challenges in quality, staffing, and accountability. InterRAI assessment instruments, used nationally ...

Trends and Scientific Evolution in Endovascular Aneurysm Repair (EVAR) Research: A Comprehensive Bibliometric Study Using VOSviewer.

BACKGROUND: Endovascular aneurysm repair (EVAR) has become a standard treatment for abdominal aortic aneurysms. However, the evolution of EVAR researc...

The escalating threat of multidrug-resistant organisms: COVID-19 impact, global burden, and the Taiwanese experience.

INTRODUCTION: The COVID-19 pandemic has intensified global health challenges, including a silent but escalating crisis: multidrug-resistant organisms ...

Trust at risk: Why public health must lead the use of AI in pandemic preparedness.

Artificial intelligence (AI) is poised to play a transformative role in pandemic preparedness, with the potential to enhance surveillance, risk assess...

Leveraging a large language model to support expansion of surveillance activities to include cardiovascular implantable device infections in a large, integrated national healthcare system.

BACKGROUND: Surveillance activities are emerging as exemplar use cases for large language models (LLMs) in health care. The aim of this study was to e...

A review of AI/ML approaches in wastewater surveillance advancement.

Wastewater-based epidemiology (WBE) has emerged as a powerful tool for early detection and monitoring of infectious diseases, particularly during pand...

The Future of Non-muscle-invasive Bladder Cancer: Towards a Molecular-Digital Paradigm for Personalized Management.

The management of non-muscle-invasive bladder cancer (NMIBC) is undergoing a major paradigm shift driven by molecular biomarkers, artificial intellige...

Managing Conflict of Interest in Clinical Practice Guidelines With Artificial Intelligence: Insights From Large Language Models and Beyond.

BACKGROUND: Conflict of interest (COI) management is critical for ensuring the scientific integrity and fairness of clinical practice guidelines (CPGs...

A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation.

Glaucoma is the leading cause of irreversible blindness worldwide with heterogeneous progression rates. Artificial Intelligence (AI) may enable accura...