Intelligent Expert Systems for Disease Diagnosis in Resource-Constrained Health Systems: A Systematic Review of Current Trends and Research Gaps

Intelligent Expert Systems for Disease Diagnosis in Resource-Constrained Health Systems: A Systematic Review of Current Trends and Research Gaps | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Intelligent Expert Systems for Disease Diagnosis in Resource-Constrained Health Systems: A Systematic Review of Current Trends and Research Gaps George Oluwatobiloba Hannah, Osaremwinda Omorogiuwa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9336112/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Design and development of artificial intelligence (AI) has transformed many sectors, one of which is healthcare, through early disease prediction, improved diagnostic accuracy, and decision support systems. However, the potential of Artificial Intelligence has not been maximized for Africans. Most existing diagnostic tools use AI models developed with data from Western populations; this has therefore limited their reliability and effectiveness when applied in African contexts. This is due to differences in genetic makeup, demography, and infrastructure. Additionally, data policy, privacy, and security concerns remain some of the major challenges in adopting AI in healthcare across Africa. This research proposes the design and development of a secured multimodal AI system capable of integrating various medical data, including laboratory results, medical images, and textual health records, to support prognostic and diagnostic decisions for African patients. This AI model will be trained with African data, enabling it to handle local medical data variations and implement robust encryption and privacy mechanisms. By solving the challenges of both data security and data bias, this research aims to enhance the fairness, effectiveness, and reliability of AI-assisted medical diagnosis within African healthcare systems. Artificial Intelligence Health Diagnosis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9336112","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628841198,"identity":"2f07bbab-4e5d-4251-84a4-92136b908dbc","order_by":0,"name":"George Oluwatobiloba Hannah","email":"data:image/png;base64,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","orcid":"","institution":"Igbinedion University","correspondingAuthor":true,"prefix":"","firstName":"George","middleName":"Oluwatobiloba","lastName":"Hannah","suffix":""},{"id":628841201,"identity":"c8e2ec5e-0fca-47b1-947e-b81589569258","order_by":1,"name":"Osaremwinda Omorogiuwa","email":"","orcid":"","institution":"Igbinedion University","correspondingAuthor":false,"prefix":"","firstName":"Osaremwinda","middleName":"","lastName":"Omorogiuwa","suffix":""}],"badges":[],"createdAt":"2026-04-06 17:10:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9336112/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9336112/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182291,"identity":"f6ebaa7c-03ed-4119-a98c-ea4bf3f71b8f","added_by":"auto","created_at":"2026-04-30 08:59:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":298376,"visible":true,"origin":"","legend":"","description":"","filename":"IntelligentExpertSystemsforDiseaseDiagnosisinResourceConstrainedHealthSystemsASystematicReviewofCurrentTrendsandResearchGaps..pdf","url":"https://assets-eu.researchsquare.com/files/rs-9336112/v1_covered_84f50cb8-b6fc-4e44-88e7-30d5ddc68a1b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Intelligent Expert Systems for Disease Diagnosis in Resource-Constrained Health Systems: A Systematic Review of Current Trends and Research Gaps","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial Intelligence, Health, Diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-9336112/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9336112/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Design and development of artificial intelligence (AI) has transformed many sectors, one of which is healthcare, through early disease prediction, improved diagnostic accuracy, and decision support systems. 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