8 Şubat 2021 Kitap bölümü Kısıtlı Erişim

Karaarslan, Enis; Konacakli, Enis

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    <subfield code="a">&lt;p&gt;Using artificial intelligence for data-driven medical diagnosis requires processing a wide variety and massive amounts of medical data collected from different resources. Resilience, controllability, and privacy of the medical data are the most important concerns for enabling AI-based data-driven medical diagnosis. Health data storage and its security and privacy requirements emerge as one of the most important challenges. The privacy concerns and lack of trust in the system became the main barrier for collecting and storing personal medical data. The patient should be given the data ownership and the track of the collected data should be kept. The privacy and security requirements of this data can be covered by using decentralized solutions. Decentralized solutions give us the opportunity of removing the intermediaries and establish trust between peers. This chapter aims to summarize the current studies and their possible impacts on the health industry and medical studies. Possible future uses of integrating blockchain with AI are given. AI can also be used to solve the challenges in blockchain and this chapter will also address some solutions.Multi-Platform Interoperable Scalable Architecture (MPISA) model for healthcare data sharing is proposed.&lt;/p&gt;</subfield>
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