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dc.contributor.authorChamola, Vinay-
dc.date.accessioned2023-03-17T09:04:20Z-
dc.date.available2023-03-17T09:04:20Z-
dc.date.issued2022-03-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/9773136-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9817-
dc.description.abstractWhile the onset of the COVID-19 pandemic has increased the popularity of home-based consultations, worries over privacy, high consultations costs, slow response times, and the burden on doctors due to the overwhelming number of COVID-19 cases have made current in-person and online models ineffective. In this study, we present an advanced, privacy-protected, artificial intelligence and blockchain-based consultation framework for minor medical conditions. Patients can post their medical queries anonymously on the blockchain network, which may be answered by any available medical professionals. The queries are sorted into their respective domains using naive Bayes and logistic regression. The consultations provided by medical specialists are evaluated based on their reputation, expertise, detail orientation, and the use of supporting documents, and rewards are given in accordance with the evaluation scheme. This fair and incentivized system provides cheaper and more accessible healthcare to patients, which is the need of the hour.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectCOVID-19en_US
dc.subjectMedical conditionsen_US
dc.subjectPandemicsen_US
dc.subjectMachine Learningen_US
dc.subjectBlockchainsen_US
dc.subjectLogisticsen_US
dc.subjectTelemedicineen_US
dc.subjectArtificial intelligence (AI)en_US
dc.titleEnabling Cost-Effective and Secure Minor Medical Teleconsultation Using Artificial Intelligence and Blockchainen_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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