Artificial Intelligence for Improved Health Management: Application, Uses, Opportunities, and Challenges-A Systematic Review | ||||
| Egyptian Journal of Chemistry | ||||
| Volume 67, Issue 13, December 2024, Page 865-880 PDF (433.51 K) | ||||
| Document Type: Review Articles | ||||
| DOI: 10.21608/ejchem.2024.319621.10386 | ||||
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| Authors | ||||
| Kholood Mohammed Yahya Moafa* 1; Nouf Falah Hindi Almohammadi1; Fatma Saeed Snhat Alrashedi1; Salwa Thamer Saleh Alrashidi1; Saud Abdullah Al-Hamdan2; Majedah Mohammad Faggad2; Sarah Mohammed Alahmary2; Mohammed Ibrahim Abdulrahman Al-Darwaish3; Asmaa Khalaf Al-Anzi3 | ||||
| 1Ministry of Defense, Armed Forces Hospital, Riyadh, Saudi Arabia | ||||
| 2King Khalid University Hospital – Riyadh, Saudi Arabia | ||||
| 3Emergency Medical Services Specialist - Prince Sultan Military Medical City – Riyadh, Saudi Arabia. | ||||
| Abstract | ||||
| Aims: This study aims to provide a comprehensive overview of the role of artificial intelligence (AI) and machine learning (ML) in various domains, particularly healthcare, and its implications for international development and public health. It seeks to explore the applications, challenges, and future directions of AI and ML technologies in shaping healthcare delivery, disease prediction, diagnosis, treatment planning, and public health interventions. Methods: The study employs a systematic review approach to synthesize the literature on AI and ML applications in healthcare, drawing insights from a wide range of sources including research articles, reports, and news articles. Various aspects of AI, such as deep learning, natural language processing, robotics, and predictive modeling, are examined to understand their potential in addressing healthcare challenges and improving health outcomes. Results: The review identifies a plethora of AI applications in healthcare, ranging from medical imaging and diagnostics to personalized medicine and predictive analytics. These technologies have demonstrated promising results in enhancing clinical decision-making, optimizing healthcare delivery, and facilitating early disease detection. However, challenges related to data privacy, algorithm bias, regulatory compliance, and ethical considerations remain significant barriers to widespread adoption. Conclusion: AI and ML hold immense potential to revolutionize healthcare delivery and public health initiatives, offering opportunities for enhanced efficiency, accuracy, and accessibility of healthcare services. Nevertheless, careful consideration of ethical, legal, and social implications is crucial to ensure responsible and equitable deployment of these technologies. Collaborative efforts among policymakers, healthcare providers, technologists, and other stakeholders are essential to harness the full benefits of AI while addressing its challenges | ||||
| Keywords | ||||
| Artificial intelligence; Public Healthcare; Ethical considerations; Predictive analytics; Deep learning; medical imaging; Personalized medicine | ||||
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