OptiSelect and EnShap: Integrating Machine Learning and Game Theory for Ischemic stroke prediction

OptiSelect and EnShap: Integrating Machine Learning and Game Theory for Ischemic stroke prediction | 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 Article OptiSelect and EnShap: Integrating Machine Learning and Game Theory for Ischemic stroke prediction Pritam Chakraborty, Anjan Bandyopadhyay, Sricheta Parui, Sujata Swain, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3841050/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 This paper presents a novel approach to predictive Ischemic brain stroke analysis using game theory and machine learningtechniques. The study investigates the use of the Shapley value in predictive Ischemic brain stroke analysis. Initially, preferencealgorithms identify the most important features in various machine learning models, including logistic regression, K-nearestneighbor, decision tree, support vector machine (linear kernel), support vector machine (RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley Valuemethod has been used to rank the models using their best four features based on their predictive capabilities. As a result,better-performing models have been found. Afterward, ensemble machine learning methods were used to find the mostaccurate predictions using the top 5 models ranked by shapely value. The research demonstrates an impressive accuracyof 92.39%, surpassing other proposed models’ performance. This study highlights the utility of combining game theory andmachine learning in Ischemic brain stroke prediction and the potential of ensemble learning methods to increase predictiveaccuracy in Ischemic stroke analysis. 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-3841050","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269705199,"identity":"6446b39d-df53-4843-842c-7648e9536e2b","order_by":0,"name":"Pritam Chakraborty","email":"","orcid":"","institution":"KIIT University","correspondingAuthor":false,"prefix":"","firstName":"Pritam","middleName":"","lastName":"Chakraborty","suffix":""},{"id":269705200,"identity":"9d868ff7-d260-4d32-b21d-232a6b225161","order_by":1,"name":"Anjan Bandyopadhyay","email":"","orcid":"","institution":"KIIT University","correspondingAuthor":false,"prefix":"","firstName":"Anjan","middleName":"","lastName":"Bandyopadhyay","suffix":""},{"id":269705201,"identity":"5aa1be9a-6717-41c5-9c86-94aaea0ea9ab","order_by":2,"name":"Sricheta Parui","email":"","orcid":"","institution":"KIIT University","correspondingAuthor":false,"prefix":"","firstName":"Sricheta","middleName":"","lastName":"Parui","suffix":""},{"id":269705202,"identity":"de52fc1b-61d3-4dfe-92d9-170dc4d1050b","order_by":3,"name":"Sujata Swain","email":"","orcid":"","institution":"KIIT University","correspondingAuthor":false,"prefix":"","firstName":"Sujata","middleName":"","lastName":"Swain","suffix":""},{"id":269705203,"identity":"648ed0d8-6b31-485b-aa69-c35a1ec75199","order_by":4,"name":"Partha Sarathy Banerjee","email":"","orcid":"","institution":"Jaypee University of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Partha","middleName":"Sarathy","lastName":"Banerjee","suffix":""},{"id":269705204,"identity":"f5f10bb8-6ad4-475a-a0bf-0f6b5c5fc1b3","order_by":5,"name":"Tapas Si","email":"","orcid":"","institution":"University of Engineering \u0026 Management","correspondingAuthor":false,"prefix":"","firstName":"Tapas","middleName":"","lastName":"Si","suffix":""},{"id":269705205,"identity":"cdef2967-e450-49b7-b8d1-e91edeb8bcab","order_by":6,"name":"Saurav Mallik","email":"","orcid":"","institution":"Harvard University","correspondingAuthor":false,"prefix":"","firstName":"Saurav","middleName":"","lastName":"Mallik","suffix":""},{"id":269705206,"identity":"ce3760a6-48dc-48b7-b4ba-f110c65a296f","order_by":7,"name":"Badria Sulaiman Alfurhood","email":"","orcid":"","institution":"Princess Nourah bint Abdulrahman University","correspondingAuthor":false,"prefix":"","firstName":"Badria","middleName":"Sulaiman","lastName":"Alfurhood","suffix":""},{"id":269705207,"identity":"12dd600d-6267-4ee3-836b-8c155615f288","order_by":8,"name":"Mohammed Azmi Al-Betar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYHACxsNgir2BwYBoPUAtQMU8B0jWIpFApHLdBuYHhwsq/sibz3z8oOhGzR0G/vYDjB8+4NFidoDN4PCMMwaGc26nGRjnHHvGIHEmgVlyBl4tDAaHedsMGGdIJwC1sAEdeYOBQZoHrxb2D4d5/xnYz5A8/sE4599hBvkbDMy//+DVwgO0pcEgcYYEj4FxbtthBoMbDGzS+Lxvdpin4PCMY8bJM3hyCoxz+w7zGJ5JbLPswaflePvGxwU1crYz2I9vM875dlhO7vjhwzd+4LOGGcFkA0Ul0OOMDfg0oOp+QLTSUTAKRsEoGFEAAO1yTg6vev2uAAAAAElFTkSuQmCC","orcid":"","institution":"Ajman University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Mohammed","middleName":"Azmi","lastName":"Al-Betar","suffix":""},{"id":269705208,"identity":"c8591805-225b-455f-a5ea-ac634f13fb54","order_by":9,"name":"Ammar Almomani","email":"","orcid":"","institution":"University of Sharjah","correspondingAuthor":false,"prefix":"","firstName":"Ammar","middleName":"","lastName":"Almomani","suffix":""}],"badges":[],"createdAt":"2024-01-07 02:00:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3841050/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3841050/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62875187,"identity":"9cb4bddc-fe5b-4f23-aa34-f41c447b2f8a","added_by":"auto","created_at":"2024-08-20 13:45:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1292559,"visible":true,"origin":"","legend":"","description":"","filename":"OptiSelectandEnShapIntegratingMachineLearningandGameTheoryforIschemicstrokeprediction4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3841050/v1_covered_b6c2a072-28db-4174-9de5-cc883cad6493.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"OptiSelect and EnShap: Integrating Machine Learning and Game Theory for Ischemic stroke prediction","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-3841050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3841050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This paper presents a novel approach to predictive Ischemic brain stroke analysis using game theory and machine learningtechniques. The study investigates the use of the Shapley value in predictive Ischemic brain stroke analysis. Initially, preferencealgorithms identify the most important features in various machine learning models, including logistic regression, K-nearestneighbor, decision tree, support vector machine (linear kernel), support vector machine (RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley Valuemethod has been used to rank the models using their best four features based on their predictive capabilities. As a result,better-performing models have been found. Afterward, ensemble machine learning methods were used to find the mostaccurate predictions using the top 5 models ranked by shapely value. The research demonstrates an impressive accuracyof 92.39%, surpassing other proposed models’ performance. This study highlights the utility of combining game theory andmachine learning in Ischemic brain stroke prediction and the potential of ensemble learning methods to increase predictiveaccuracy in Ischemic stroke analysis.","manuscriptTitle":"OptiSelect and EnShap: Integrating Machine Learning and Game Theory for Ischemic stroke prediction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-29 18:27:29","doi":"10.21203/rs.3.rs-3841050/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"b4c5ee53-eb30-444c-801a-e0e16a0c55e0","owner":[],"postedDate":"January 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-02T06:36:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-29 18:27:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3841050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3841050","identity":"rs-3841050","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}