All Stories

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