All Stories

  1. District-level measles outbreak prediction in Bangladesh using geospatial artificial intelligence
  2. Stillbirth, Neonatal, and Child Mortality in Bangladesh: Progress and Persistent Public Health Challenges
  3. Enhancing Diaspora Scientist Identification Through SMOTE ‐Driven Machine Learning and Transformer‐Based Hybrid Models on Multi‐Institution Dataset
  4. Spatiotemporal patterns of climate-sensitive vector-borne diseases in Bangladesh: leveraging machine learning and spatial regression for intervention strategies
  5. District-Level Dengue Early Warning Prediction System in Bangladesh Using Hybrid Explainable AI and Bayesian Deep Learning
  6. Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
  7. Acceptance of E-health in Bangladesh: An Overview
  8. Leveraging explainable artificial intelligence and spatial analysis for communicable diseases in Asia (2000–2022) based on health, climate, and socioeconomic factors
  9. Knowledge and beliefs about climate change and emerging infectious diseases in bangladesh: implications for one health approach
  10. Unraveling global malaria incidence and mortality using machine learning and artificial intelligence–driven spatial analysis
  11. Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model
  12. Utilizing artificial intelligence to predict and analyze socioeconomic, environmental, and healthcare factors driving tuberculosis globally
  13. Impact of Climate Change on Emerging Infectious Diseases and Human Physical and Mental Health in Bangladesh
  14. Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh
  15. Spatio‐temporal pattern and associate meteorological factors of airborne diseases in Bangladesh using geospatial mapping and spatial regression model
  16. Predicting anxiety, depression, and insomnia among Bangladeshi university students using tree‐based machine learning models
  17. Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model
  18. A quantile regression approach to identify risk factors for high blood glucose levels among Bangladeshi individuals
  19. A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study
  20. A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study (Preprint)
  21. Risk factors of caesarean deliveries in urban–rural areas of Bangladesh
  22. The experiences of district public health officers during the COVID-19 crisis and its management in the upper southern region of Thailand: A mixed methods approach
  23. Understanding dengue solution and larval indices surveillance system among village health volunteers in high- and low-risk dengue villages in southern Thailand
  24. Epidemiological profile of dengue in Champasak and Savannakhet provinces, Lao People’s Democratic Republic, 2003–2020
  25. A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological drivers
  26. Role of artificial intelligence-internet of things (AI-IoT) based emerging technologies in the public health response to infectious diseases in Bangladesh
  27. Accuracy comparison of ARIMA and XGBoost forecasting models in predicting the incidence of COVID-19 in Bangladesh
  28. Mapping the spatial distribution of the dengue vector Aedes aegypti and predicting its abundance in northeastern Thailand using machine-learning approach
  29. Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand
  30. Analyzing Predictors of Control Measures and Psychosocial Problems Associated with COVID-19 Pandemic: Evidence from Eight Countries
  31. Ecological, Social, and Other Environmental Determinants of Dengue Vector Abundance in Urban and Rural Areas of Northeastern Thailand
  32. Correction: Doum, D., et al. Dengue Seroprevalence and Seroconversion in Urban and Rural Populations in Northeastern Thailand and Southern Laos. Int. J. Environ. Res. Public Health 2020, 17, 9134
  33. Knowledge, attitudes, and practices on climate change and dengue in Lao People's Democratic Republic and Thailand
  34. COVID-19 Epidemic in Bangladesh among Rural and Urban Residents: An Online Cross-Sectional Survey of Knowledge, Attitudes, and Practices
  35. Dengue Seroprevalence and Seroconversion in Urban and Rural Populations in Northeastern Thailand and Southern Laos
  36. Climate change and dengue fever knowledge, attitudes and practices in Bangladesh: a social media–based cross-sectional survey
  37. Defending against the Novel Coronavirus (COVID-19) outbreak: How can the Internet of Things (IoT) help to save the world?
  38. Survival probabilities of stomach and colon cancer patients in Bangladesh
  39. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?
  40. Forecasting the BDT/USD Exchange Rate: An Accuracy Comparison of Artificial Neural Network Models and Different Time Series Models
  41. Weak Form, Run test, Autocorrelation test, Variance Ratio Test, CSE.