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Leveraging AI and Big Data for Predictive Healthcare in Public Administration in Malaysia
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Author(s): Mohammad Ibrahim Khan (International Medical University, Malaysia), Nurqistina Balqis (International Medical University, Malaysia), Arshi Naim (European Global Institute of Innovation and Technology, Malta), Hesham Magd (University of Wolverhampton, UK), Praveen Kumar Malik (Lovely Professional University, India)and Mohammad Faiz Khan (MInistry of Interiors, Saudi Arabia)
Copyright: 2026
Pages: 20
Source title:
Digital Technologies and Transformations in Public Administration, Engineering, and Sustainable Business
Source Author(s)/Editor(s): Arshi Naim (European Global Institute of Innovation and Technology, Malta), Anuj Kumar (Rushford Business School, Switzerland)and Arya Kumar (KIIT University, India)
DOI: 10.4018/979-8-3373-1534-8.ch004
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Abstract
The current research works for the integration of Artificial Intelligence (AI) and Big Data analytics in public healthcare administration. The focus of the integration is on their predictive capabilities. The research methodology primarily employs secondary data analysis sourced from the United Nations and other reputable healthcare reports relevant to Malaysia. The study has analyzed the secondary data which examines how AI-driven models and Big Data are being utilized to forecast health outcomes, optimize resource allocation, and enhance decision-making processes in government-run healthcare systems in the country Malaysia. This research method builds for an in-depth evaluation of the effectiveness of these technologies in predicting diseases, managing public health crises, and reducing healthcare costs. The findings aim to show the potential of AI and Big Data in transforming healthcare systems to become more proactive, efficient, and sustainable. The outcomes of the study present the healthcare services in Malaysian public healthcare administration.
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