Concept: Data-Driven Disease Surveillance
Social life of HIV data
Exploring power, equity, and ethics in HIV data collection and use
District-Level Dengue Early Warning Prediction System in Bangladesh Using Hybrid Explainable AI and Bayesian Deep Learning
Predicting dengue outbreaks across Bangladesh districts using climate and socioeconomic data
Image Credit: AI-generated image (OpenAI / DALL·E)How to ensure effective and sustainable ILI surveillance in Belgian general practices? : protocol
Designing automated illness tracking for Belgian doctor offices
A Standardized Statistical Framework for Population Surveillance Using the National Health Interview Survey
A framework for consistent and comparable health estimates across studies
Data-driven model analysis of the impact of environmental and socioeconomic factors on tuberculosis incidence
Environmental and economic conditions drive tuberculosis rates in Taiwan
Big Data and Machine Learning Applications for Enhanced U.S. Infectious Disease Surveillance and Control: A Narrative Review
How artificial intelligence and large datasets are making disease tracking faster and more accurate
Survey on mathematical modeling of infectious disease dynamics: insights and applications
How math helps predict outbreaks and evaluate disease control strategies
Comprehensive representation of health-related phenotypes in one million dogs using topic modelling of electronic health records
Machine learning reveals disease patterns across one million dogs from veterinary records
Data generation and modeling during COVID-19: utility, barriers, and priorities for future investments in public health response
Insights from 112 public health professionals on data tools, challenges, and investment priorities
