Emmanuel Kusi Achampong
Department of Medical Education and IT School of Medical Sciences University of Cape Coast Cape Coast Ghana

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A systematic review of artificial intelligence-based methods in healthcare Apio, Anthony Lirase; Kissi, Jonathan; Achampong, Emmanuel Kusi
International Journal of Public Health Science (IJPHS) Vol 12, No 3: September 2023
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v12i3.22298

Abstract

Artificial intelligence (AI) in healthcare has enormous potential for transforming healthcare. AI is the ability of machines to learn and exhibit close to human levels of cognition in various specific ways. Leveraging AI software to support activities will improve patient satisfaction which is inextricably tied to the length of time patients spend in waiting queues. Literature searches were conducted in PubMed, Research Gate, BMC Health Services Research, JMIR Publications and Cochrane Central to find related documentation that was published between January 2011 and April 2021. The studies featured and reported on AI technologies that had been used in primary, secondary, or tertiary healthcare situations directed towards reducing waiting times. A total of 22 articles were primarily used, including 8 retrospective studies, 4 prospective studies and 3 case-control studies. AI technologies have enormous potential in the creation of a future with more reliable healthcare systems. It is however clear that more studies in the field are required to validate the existing evidence of its potential. AI in healthcare is crucial to reducing patients' time at healthcare facilities. The use of AI can also help improve patient outcomes and more research should be geared toward that.