A Systematic Review of the Outcomes of Utilization of Artificial Intelligence Within the Healthcare Systems of the Middle East: A Thematic Analysis of Findings.

Mohsen Khosravi, Seyyed Morteza Mojtabaeian, Emine Kübra Dindar Demiray, Burak Sayar
Author Information
  1. Mohsen Khosravi: Imam Hossein Hospital Shahroud University of Medical Sciences Shahroud Iran. ORCID
  2. Seyyed Morteza Mojtabaeian: Department of Healthcare Services Management, School of Management and Medical Informatics Shiraz University of Medical Sciences Shiraz Iran.
  3. Emine Kübra Dindar Demiray: Afyonkarahisar Public Hospital Infectious Diseases and Clinical Microbiology Afyonkarahisar Turkey.
  4. Burak Sayar: Bitlis Eren University Vocational School of Social Sciences Bitlis Türkiye.

Abstract

Background and Aims: The rapid expansion of artificial intelligence (AI) within worldwide healthcare systems is occurring at a significant rate. In this context, the Middle East has demonstrated distinctive characteristics in the application of AI within the healthcare sector, particularly shaped by regional policies. This study examined the outcomes resulting from the utilization of AI within healthcare systems in the Middle East.
Methods: A systematic review was conducted across several databases, including PubMed, Scopus, ProQuest, and the Cochrane Database of Systematic Reviews in 2024. The quality assessment of the included studies was conducted using the Authority, Accuracy, Coverage, Objectivity, Date, Significance checklist. Following this, a thematic analysis was carried out on the acquired data, adhering to the Boyatzis approach.
Results: 100 papers were included. The quality and bias risk of the included studies were delineated to be within an acceptable range. Multiple themes were derived from the thematic analysis including: "Prediction of diseases, their diagnosis, and outcomes," "Prediction of organizational issues and attributes," "Prediction of mental health issues and attributes," "Prediction of polypharmacy and emotional analysis of texts," "Prediction of climate change issues and attributes," and "Prediction and identification of success and satisfaction among healthcare individuals."
Conclusion: The findings emphasized AI's significant potential in addressing prevalent healthcare challenges in the Middle East, such as cancer, diabetes, and climate change. AI has the potential to overhaul the healthcare systems. The findings also highlighted the need for policymakers and administrators to develop a concrete plan to effectively integrate AI into healthcare systems.

Keywords

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Word Cloud

Created with Highcharts 10.0.0healthcare"PredictionAI"withinsystemsMiddleEastincludedanalysisissuesattributesartificialintelligencesignificantoutcomesconductedSystematicqualitystudiesthematicdatahealthclimatechangefindingspotentiallearningBackgroundAims:rapidexpansionworldwideoccurringratecontextdemonstrateddistinctivecharacteristicsapplicationsectorparticularlyshapedregionalpoliciesstudyexaminedresultingutilizationMethods:systematicreviewacrossseveraldatabasesincludingPubMedScopusProQuestCochraneDatabaseReviews2024assessmentusingAuthorityAccuracyCoverageObjectivityDateSignificance checklistFollowingcarriedacquiredadheringBoyatzisapproachResults:100papersbiasriskdelineatedacceptablerangeMultiplethemesderivedincluding:diseasesdiagnosisorganizationalmentalpolypharmacyemotionaltextsidentificationsuccesssatisfactionamongindividuals"Conclusion:emphasizedAI'saddressingprevalentchallengescancerdiabetesoverhaulalsohighlightedneedpolicymakersadministratorsdevelopconcreteplaneffectivelyintegrateReviewOutcomesUtilizationArtificialIntelligenceWithinHealthcareSystemsEast:ThematicAnalysisFindingsminingdeeppolicymachine

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