AI-Driven Public Health Infrastructure: Developing a Framework for Transformative Health Outcomes in the United States

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@article{1706317,
      author = {Pelumi Oladokun, Azeezat Oluwakemi Sule, Moyosoreoluwa Ogundipe, Temidayo Osinaike},
      title = {AI-Driven Public Health Infrastructure: Developing a Framework for Transformative Health Outcomes in the United States},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {3},
      pages = {510-520},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706317.pdf},
      abstract = {The effective, efficient, and equitable delivery of healthcare in the United States can be greatly improved by integrating artificial intelligence (AI) into public health infrastructure. AI provides strong capabilities for data analysis, predictive modeling, and customized interventions as chronic diseases, pandemics, and health inequities pose growing difficulties to public health systems.  This research review explores how AI may transform public health infrastructure and thoroughly examines the elements required for developing an effective, AI-driven public health system. The review highlights several essential elements of an AI-powered public health infrastructure. The report also highlights the major obstacles to AI adoption. A well-structured approach to risk mitigation is crucial, as evidenced by case studies of successful AI applications. the integration of AI into public health infrastructure has the potential to revolutionize healthcare in the United States, resulting in better health outcomes and increased resilience to emerging health issues.},
      keywords = {Healthcare, Health Outcomes, Health Systems, Artificial Intelligence, Innovation},
      month = {September},
  }