Infectious Disease

Public Health

Latest AI and machine learning research in public health for healthcare professionals.

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Automated Extraction of Mortality Information from Publicly Available Sources Using Language Models

Mortality is a critical variable in healthcare research, especially for evaluating medical product s...

A simple feed forward neural network to predict the 2025 outbreak of measles in the USA

Measles is a highly contagious viral disease associated with a variety of severe complications. Sinc...

Fine-tuned large language models enhance influenza forecasting

Influenza-like illness (ILI) continues to present significant challenges to global health, highlight...

Clinicodemographic Prediction of Overall Survival in Patients with Head and Neck Merkel Cell Carcinoma: A Machine Learning Approach

Merkel cell carcinoma (MCC) is a rare cutaneous neuroendocrine malignancy with a higher case-fatalit...

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL METHODS FOR MODELLING AND FORECASTING INFLUENZA AND INFLUENZA-LIKE ILLNESS: A SCOPING REVIEW

The persistnt resurgence of influence and influenza-like illness despite concerted vaccination inter...

Fast and Trustworthy Nowcasting of Dengue Fever: A Case Study Using Attention-Based Probabilistic Neural Networks in São Paulo, Brazil

Nowcasting methods are crucial in infectious disease surveillance, as reporting delays often lead to...

AI-Enabled Diagnostic Prediction within Electronic Health Records to Enhance Biosurveillance and Early Outbreak Detection

Detecting infectious disease outbreaks promptly is crucial for effective public health responses, mi...

Outbreak and Postnatal Antibiotic Exposures Drive the Development Trajectory of the Nasopharyngeal Microbiota in the First Year of Life

Early exposure to antibiotics and prolonged hospitalization in preterm infants may perturb microbiom...

Dengue forecasting and outbreak detection in Brazil using LSTM: integrating human mobility and climate factors

Dengue fever is a major global health concern, with Brazil experiencing recurrent and severe outbrea...

Mapping Inequities in Global Vaccine Sentiment Research

Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectivenes...

Granular Insights:A Wastewater-Based Machine Learning Approach for Localized COVID-19 Hospitalization Forecasting

Wastewater based epidemiology (WBE) is a valuable tool for monitoring emerging disease trends in a c...

Multi-model approach to understand and predict past and future dengue epidemic dynamics

Understanding the past, current, and future dynamics of dengue epidemics is challenging yet increasi...

Enhancing Cause of Death Prediction: Development and Validation of ML Models Using Multimodal Data Across Multiple Healthcare Sites

Timely and accurate determination of causes of death (CoD) is essential for public health surveillan...

Design and Implementation of an End-to-End AI-Driven Colonoscopy Recall Workflow at Scale

We present a real-world deployment of a large language model-powered colonoscopy recall pipeline tha...

Enhanced machine learning and hybrid ensemble approaches for coronary heart disease prediction

Coronary heart disease (CHD) remains the leading cause of mortality worldwide, disproportionately af...

Case-Control Matching Erodes Feature Discriminability for AI-driven Sepsis Prediction in ICUs: A Retrospective Cohort Study

Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection...

Automating Handwritten Vaccination Record Transcription with Generative Multimodal AI Models: A Proof of Concept Study from The Gambia

Handwritten home-based vaccination records (HBRs) are a vital source of immunization data, yet manua...

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