Public Health

Enhancing respiratory virus surveillance among hospitalised children: a machine learning-based predictive model.

BACKGROUND: Viral respiratory tract infections (vRTIs) are a leading cause of paediatric hospitalisation and healthcare utilisation. Existing syndromic surveillance tools, including the WHO Severe Acute Respiratory Infection definition, demonstrate limited diagnostic accuracy in children whose symptom profiles vary widely. This study aimed to develop a machine learning (ML) model to predict microb...

Data fusion in air pollution exposure assessment: Methods, applications, and future directions.

Over the past two decades, major advances in observational techniques and modeling capabilities have enabled the development of air pollution data fusion methods that integrate information from regulatory monitoring networks, low-cost sensors, satellite remote sensing, and chemical transport models (CTMs). These approaches combine measurements from regulatory monitoring networks with complementary...

Antibiotic therapy in febrile neutropenia in haematological patients: current considerations and future challenges.

The management of febrile neutropenia (FN) in oncohematological patients is undergoing a paradigm shift driven by a deeper understanding of patients' ...

Unveiling Viral Escape Mechanisms With Machine Learning: A Transformative Approach to Mutation Analysis for SARS-CoV-2 and Beyond.

Persistent viruses like Influenza, HIV, and Coronavirus exemplify the challenge of viral escape, significantly hindering the development of long-lasti...

Disease and Health Surveillance in Companion Animals Using Artificial Intelligence and Machine Learning.

Companion animal disease surveillance now benefits from collated databases of electronic health records and artificial intelligence. This review exami...

The One Health resistome: Integrating environmental, microbial, and human antimicrobial resistance surveillance and risk analysis in the digital age.

Antimicrobial resistance (AMR) and antibiotic resistance (ABR) represent one of the most pressing global health threats, driven by the complex interpl...

A Dynamic Machine Learning Approach to Complement Nurse-Led Clinics in Identifying High-Risk Patients with Intermittent Claudication.

OBJECTIVE: To develop and validate dynamic machine-learning models to predict 6-month adverse outcomes in intermittent claudication (IC), enabling ris...

Evaluation and enhancement of the prognostic ability of the eighth edition of TNM staging in cutaneous malignant melanoma: a population-based study, using machine learning, of 111 871 patients.

BACKGROUND: Melanoma is the fifth most common cancer in the USA and the UK, with global incidence on the rise. The TNM staging system guides treatment...

Prospects and Challenges of Personalized Immunotherapy in Breast Cancer Treatment and Long-term Cancer Management.

Breast cancer is highly heterogeneous,and different molecular subtypes exhibit significant variations in their response to immunotherapy.While signifi...

Augmenting prion surveillance by immunohistochemistry using artificial intelligence-based image analysis.

Chronic wasting disease (CWD) and scrapie are transmissible spongiform encephalopathy diseases caused by prions, infectious forms of the prion protein...

Synonymous mutations in viral evolution and vaccine design.

Synonymous mutations, long regarded as evolutionarily neutral, are increasingly recognized as important determinants of viral evolution and adaptation...

A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning.

Respiratory disease outbreaks burden American healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag...

A novel lexicon dictionary and CNN-LSTM employed hybrid approach for sentiment detection of COVID-19 vaccines.

With the rapid advancement of the internet, social media has become an integral part of human life. It provides a soothing platform for people to shar...

Analysis, control, and forecasting the dynamics of SIRD models with saturated treatment and nonlinear incidence.

This study addresses the challenge of managing complex epidemic dynamics exhibited by a novel Susceptible-Infected-Recovered-Deceased (SIRD) model. Th...

From data to decision: a clinical pipeline for wearable AI in early cardiotoxicity detection.

Chemotherapy-induced cardiotoxicity (CIC) is a leading cause of morbidity in cancer survivors, as conventional surveillance often detects cardiac dysf...

Global whole-genome, phylodynamic, and machine-learning analysis of Glaesserella parasuis serovars 2, 5, and 12.

Glaesserella parasuis is a respiratory pathogen of swine and the causative agent of Glässer's disease. Among the 15 serotypes, serotypes 2, 5, and 12 ...

The role of whole genome sequencing in antimicrobial susceptibility prediction of bacteria: 2025 update from the EUCAST Subcommittee.

SCOPE: The 2017 European Committee on Antimicrobial Susceptibility Testing (EUCAST) subcommittee report on the role of Whole Genome Sequencing (WGS) i...

Unveiling the gap in heart failure: a Brazilian Unified Health System study.

BACKGROUND: Heart failure (HF) decompensation is the leading cause of hospitalisations in developed countries and the third most common cause in Brazi...

Evaluating Crowdsourced Data Collection for Carceral Death Surveillance: Pilot Study Using Amazon Mechanical Turk.

BACKGROUND: People who are incarcerated face significantly higher health risks than the general population, yet deaths in custody remain underreported...

Leveraging artificial intelligence to predict non-adherence to pediatric immunization schedules: a systematic review.

UNLABELLED: Immunization is one of the most effective interventions to prevent infectious diseases. Identifying individuals at risk of non-adherence t...