Surveillance

AI-Driven Activity of Daily Living Monitoring: A Comprehensive Review of Ambient, Wearable, and Fusion-Based Sensing Technologies.

The increasing prevalence of chronic diseases, functional decline, and cognitive impairments, together with the limitations of episodic clinical assessments, has created a critical need for automated and continuous monitoring of Activities of Daily Living (ADLs) to support timely intervention, personalized care, and independent living. This review systematically examines how ambient sensing, weara...

Integrating explainable AI and One Health: a new frontier in combating infectious diseases.

Infectious diseases (IDs) remain a major threat to global health and societal stability. Because most emerging IDs in humans are zoonotic in origin and shaped by environmental contexts, effective prevention and control call for a One Health approach. Machine learning is widely used for ID modelling and forecasting but often lacks interpretability to explain predictions or guide public health actio...

Artificial intelligence for diagnosis and triage in oral cancer: a clinician‑centered narrative review.

BACKGROUND: Early diagnosis of oral squamous cell carcinoma (OSCC) remains challenging, with survival largely stage-dependent at presentation. Artific...

The Microbial Mechanisms of Cardiovascular Disease: Oral Dysbiosis as a Systemic Instigator.

Oral dysbiosis, particularly through periodontal disease, links strongly to cardiovascular risks by driving chronic inflammation and microbial translo...

Mathematical modelling and analysis of human metapneumovirus transmission dynamics using neural network intelligence and optimal control.

Human metapneumovirus (hMPV) is a serious global health threat because it causes human respiratory diseases in people of all ages. The complicated dyn...

Automation Software for Transesophageal Echocardiography in Cardiac Patients: A Scoping Review.

Automation software has improved accuracy, efficiency, and reproducibility in transthoracic echocardiography, but its role in transesophageal echocard...

Evaluating the ability of generative AI to standardize TNM staging data in lung cancer.

This study evaluates the ability of generative artificial intelligence (AI) models to standardize tumor-node-metastasis (TNM) staging data in lung can...

Predictive proteomics: Binary classification of Streptococcus pneumoniae vaccine types via MALDI-TOF MS and supervised learning algorithms.

INTRODUCTION: Laboratory surveillance of Streptococcus pneumoniae serotypes is crucial for the effective implementation of vaccines against invasive p...

A lightweight transformer-based hybrid encoder-decoder model for chest X-ray medical report generation.

Diagnosing diseases from medical images and reporting them at the paragraph level is a significant challenge for deep learning-based autonomous system...

Informatics for Infection Prevention and Control.

Computer informatics is integral to infection control, a role that will grow as surveillance and reporting become increasingly automated. Surveillance...

Metrics for Artificial Intelligence in Medicine: A Reference Resource.

The effective integration of artificial intelligence (AI) systems into clinical medicine depends on comprehensive and transparent performance evaluati...

Machine learning-based 4-domain framework for evaluating COVID-19 policy responses: a counterfactual analysis of 27 European OECD countries.

OBJECTIVES: European countries implemented highly diverse mitigation policies during the COVID-19 pandemic, ranging from strict nationwide lockdowns t...

Artificial intelligence-based prognostic models in acute myeloid leukemia: systematic review and meta-analysis.

Machine learning and deep learning tools have been proposed to improve survival prediction in acute myeloid leukemia (AML), but comparative benchmarks...

Diagnostic, predictive, and therapeutic approaches for impacted canines: a systematic review and meta-analysis.

OBJECTIVE: Maxillary canine impaction affects approximately 1-3% of the population and presents diagnostic, prognostic, and therapeutic challenges. Th...

Advances in Pathogen Detection by Nanosensors: Biorecognition Strategies, Signal Amplification, and Platform Engineering.

The escalating global threat of infectious diseases, compounded by antimicrobial resistance (AMR), calls for improved diagnostic strategies. Conventio...

Staphylococcus aureus resistance to non-β-lactam antibiotics: global genomic epidemiology and machine learning feasibility assessment.

Staphylococcus aureus is increasingly resistant to β-lactam antibiotics, making non-β-lactam cell-wall-targeting drugs crucial alternatives. Growing r...

Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities.

OBJECTIVES: To analyse the landscape of active US National Institutes of Health (NIH) artificial intelligence (AI) health research grants, with emphas...

[The evolution of antimicrobial therapy for sepsis].

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host immune response to infection, representing a critical global public healt...

Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.

Artificial intelligence (AI) is increasingly used in mental health, yet its rehabilitation-oriented applications in schizophrenia have not been system...

Effects of long-term exposure to nitrogen dioxide with cardiovascular mortality: Evidence from a nationwide cohort study.

Nitrogen dioxide (NO2) is a significant ambient pollutant whose independent health effects have not been well confirmed. Evidence on the relationship ...