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Machine Learning and Text Mining for Advanced Information Sharing Systems in Blockchain and Cybersecurity Applications

This research explores the role of blockchain technology in advanced information sharing systems with the applications of energy systems and healthcare. Essay 1 proposes a blockchain application to improve resilience in smart grids by addressing cyber security and peer-to-peer trading potentials. The results show that blockchain-based smart contracts are positively related to smart grid resilience. The findings also show that blockchain-based smart contracts significantly contribute to zero trust cybersecurity, which results in a better capability to mitigate cyber-attacks. Essay 2 proposes a blockchain application to improve electronic health record (EHR) systems by increasing patient's empowerment. Confirmatory factor analysis is used for the validity and reliability tests of the model. The results show that blockchain-based information systems can empower patients by providing the perception of control over their health records. The usage of blockchain technology motivates patients to share information with healthcare provider systems and has the advantage of reducing healthcare costs and improving diagnosis management. Essay 3 contributes to the existing literature by using a multimethod approach to propose three new mediators for blockchain-based healthcare information systems: digital health care, healthcare improvement, and peer-to-peer trade capability. Based on the findings from the text analysis, we propose a research model drawing upon stimulus-organism-response theory. Through three experimental studies, we test the research model to explain the patient's willingness to share their health records with others, including researchers. A post hoc analysis is conducted to segment patients and predict their behavior using four machine learning algorithms. The finding was that merely having peer-to-peer trade capability by ignoring healthcare improvement does not necessarily incentivize patients to share their medical reports.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc2356255
Date07 1900
CreatorsHajian, Ava
ContributorsPrybutok, Victor, Chang, Hsia-Ching, Koh, Chang, Prybutok, Gayle
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Hajian, Ava, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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