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ORIGINAL RESEARCH article

Front. Public Health
Sec. Public Health Policy
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1514904

THE ROLE OF AI IN OPTIMIZING PUBLIC HEALTH POLICY AND RESOURCE ALLOCATION

Provisionally accepted
Osman Ahmed Osman Ahmed 1*Elsayed Abdalrahman Abdelrahman Elsayed Abdalrahman Abdelrahman 2Jawaher Mohammed Jawaher Mohammed 3Asma Sirageldin Ahmed Asma Sirageldin Ahmed 2
  • 1 University of Khorfakkan, Khorfakkan, United Arab Emirates
  • 2 University of Science and Technology of Fujairah, Fujairah, United Arab Emirates
  • 3 Africa International University, Khartoum, Sudan

The final, formatted version of the article will be published soon.

    This research explores the multifaceted role of AI in enhancing the strategic formulation of health policies and the optimization of resource distribution, crucially focusing on predictive analytics, machine learning, and data-driven decision-making processes. This research contributes to the discourse on AI's transformative potential in public health, advocating for a balanced approach that leverages AI's strengths while addressing its challenges, ultimately aiming to enhance public health outcomes and promote equity in healthcare access and delivery.The methodology chosen for this research adopts a mixed-methods approach to thoroughly investigate the role of artificial intelligence (AI) in optimizing public health policy and resource allocation. Primary data sources include health records, which offer insights into patient demographics, disease prevalence, and outcomes of health interventions.An important finding of the research is that the integration of AI technologies into public health policies and practices holds the promise of transforming the way health risks are managed, outbreaks are predicted, and health policies are devised, leading to improved health outcomes on a global scale.

    Keywords: artificial intelligence, public health policy, Resource Allocation, predictive analytics, machine learning, Healthcare equity

    Received: 21 Oct 2024; Accepted: 30 Dec 2024.

    Copyright: © 2024 Ahmed, Abdelrahman, Mohammed and Ahmed. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Osman Ahmed, University of Khorfakkan, Khorfakkan, United Arab Emirates

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.