Tag: Data-Driven Disease Surveillance
SIMG had marginal usability and low uptake among pregnant women
Telehealth pregnancy monitoring tool shows usability challenges despite user interest
U.S. cancer mortality declines varied by county income and location
Geographic and income gaps in U.S. cancer mortality improvements
Machine-learning algorithms improved smoking identification in health records
Machine learning improves smoking detection in health administrative records
Participants weighed privacy against potential value of browsing history research
Patient perspectives on sharing web browsing data for cancer research
H5N1 risk expanded across regions after 2020
Shifting environmental drivers of avian flu outbreaks reveal expanding risk zones
XGBoost outperformed ARIMA and Prophet for TB forecasting
Machine learning improves tuberculosis forecasting in coastal cities
District-level dengue predictions improved with climate and health data
Predicting dengue outbreaks across Bangladesh districts using climate and socioeconomic data
Image Credit: AI-generated image (OpenAI / DALL·E)Protocol compares two systems for Belgian ILI surveillance
Designing automated illness tracking for Belgian doctor offices
Machine-learning models identified key factors linked to TB incidence
Environmental and economic conditions drive tuberculosis rates in Taiwan
Topic modelling revealed known and potential canine disease phenotypes
Machine learning reveals disease patterns across one million dogs from veterinary records
