Public Health & Policy

Capturing the Mutational Dynamics of SARS-CoV-2 with Graphs

The rapid evolution of SARS-CoV-2 presents significant challenges for modeling viral dynamics, driven by lineage diversification and region-specific mutation patterns. While phylogenetic trees are traditionally used for evolutionary inference, the massive volume of SARS-CoV-2 genomic data, with many similar sequences and few distinguishing mutations, poses computational and methodological limitati...

An AI for an AI: identifying zoonotic potential of avian influenza viruses via genomic machine learning

Avian influenza remains a serious risk to human health via zoonotic transmission, as well as a feasible pandemic threat. Although limited zoonotic cases have resulted from the current epizootic outbreak, the wide diversity of influenza viruses in avian hosts means the emergence of new strains that could transmit to humans more readily cannot be ruled out. There is therefore a need to anticipate zo...

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients ...

Structurally Informed Fitness Landscapes for Surveillance of Emerging PRRSV Variants

Antibodies play a central role in neutralizing pathogens through direct interference with viral entry and recruitment of effector immune cells. Howeve...

Hybrid Epidemic–Neuronal Dynamics: A SEIR–FitzHugh–Nagumo Model for Information Flow in Complex Neural Networks

Information transfer in neural systems is often modeled through diffusive or synaptic mechanisms that fail to capture the contagion-like propagation o...

Deciphering the Antigenic Evolution of Seasonal Influenza A Viruses with PREDAC-Transformer: From Antigenic Clustering to Key Site Identification

Seasonal influenza viruses undergo continuous antigenic drift due to mutations in the hemagglutinin (HA) protein, rendering vaccines ineffective and p...

Machine learning–assisted selection of informative loci for strain-level phylogenetics of Neisseria gonorrhoeae

Epidemiological surveillance of Neisseria gonorrhoeae is hindered by the limitations of existing molecular typing methods, such as NG-MAST and MLST, w...

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...

Explainable Machine Learning for Preoperative Relapse Prediction in Molecularly Stratified Endometrial Cancer: A Single-Center Finnish Cohort Study

Relapse risk in endometrial carcinoma (EC) is strongly influenced by molecular subtype, yet current WHO/ESGO classifications rely on postoperative dat...

Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To...

Study Research Protocol for Phenome India-CSIR Health Cohort Knowledgebase (PI-CHeCK): A Prospective multi-modal follow-up study on a nationwide employee cohort

Predicting individual health trajectories based on risk scores can help formulate effective preventive strategies for diseases and their complications...

Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques

Mosquito-borne diseases cause millions of deaths each year and are increasingly spreading from tropical and subtropical regions into temperate zones, ...

SLaM Image Bank – a real-world diverse London cohort linking brain MRI to electronic mental health and dementia records for the development of clinical decision support tools using artificial intelligence

Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...

Large language models’ interpretation homogeneity and text Analysis: Evaluating the utility of the global flu view platform for Influenza surveillance

The advent of Large Language Models (LLMs) has transformed natural language processing and offers new possibilities for analyzing qualitative data in ...

Artificial Intelligence Generated Computed Tomography Segmentation of Thoracoabdominal Aorta

The rising global burden of cardiovascular diseases (CV) highlights the critical need for efficiency in disease diagnosis and management. An important...

Utilization Analysis and Fraud Detection in Medicare via Machine Learning

Healthcare fraud and overutilization pose significant challenges in the United States, leading to substantial financial losses and compromised patient...

Surveying the Literature on Implementation Determinants and Strategies for HIV Structural Interventions: A Systematic Review Protocol

Despite improvements in HIV prevention, treatment, and surveillance, vast disparities remain in access, uptake, and adherence of evidence-based interv...

AI-Driven Early Detection of Severe Influenza in Jiangsu, China: A Deep Learning Model Validated Through The Design of Multi-Center Clinical Trials and Prospective Real-World Deployment

Influenza causes about 650,000 deaths worldwide each year, and the high mortality rate of severe cases is closely related to subjective bias in clinic...

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...

PH-LLM: Public Health Large Language Models for Infoveillance

The effectiveness of public health intervention, such as vaccination and social distancing, relies on public support and adherence. Social media has e...