Big Data Analytics and Intelligent Computing for Public Health: A Review of Machine Learning, Deep Neural Networks, and Emerging Computer Science Techniques

Advanced data processing, predictive modeling, and automated decision-making are revolutionizing public health with the use of big data analytics and intelligent computing. The present review discusses the various machine learning techniques, deep neural networks, and emerging computer science methods used for disease surveillance, epidemic forecasting, chronic disease management, and population health assessment. Discusses federated learning, edge computing, graph neural networks, and generative AI and their advantages and uses. Some of the challenges are ensuring data privacy, addressing algorithmic bias, facilitating interoperability, tackling computational complexity, and ensuring model interpretability. Finally, gaps in the research and future directions for the development of reliable, scalable, transparent, and equitable intelligent public health systems around the world are identified.