Blockchain is the significant cutting-edge technology and inventive advances currently with an important function in the professional world. The exponential growth of blockchain technology has opened new application possibilities as in field of healthcare. The proposed system outlines a decentralised e-healthcare application framework for user-owned and accessible personal data management. The incorporation of cutting-edge techniques as big data, blockchain has boosted medical innovation along global development and enhanced design. The proposed model utilizes interpretive structure modelling (ISM) split order based on theoretical concepts, manage the intricate interactions between different elements and attributes which utilizes fuzzy set theory technique to remove not necessary attributes. The observation findings indicate firstly that the system's root causes include the first-level design, management of medical information, and the organisation of doctors. Secondly, key to system improvement is application optimisation. The unique intelligent contracts are at the heart of most blockchain applications in the smart healthcare space, which is dependent on the arrangement of medical information, but it is limited by system. Thirdly, development of system and effective protection of stakeholders' interests are protected by medical insurance, environmental governance, and internal and external legislation. Fourthly, blockchain application system for smart healthcare must be constructed using three consecutive layers such as the layer containing transaction, layer integrating data, and layer with stakeholder. The development in blockchain applications for smart healthcare is implemented by a theoretical hierarchical structure.


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    Titel :

    An Intelligent HealthCare System Using Blockchain Techniques


    Beteiligte:
    Deepika, J. (Autor:in) / Akilandeswari, J. (Autor:in) / B, Lokeshwaran (Autor:in) / N, Mukilarasan (Autor:in) / S, Naveen (Autor:in) / A, Prabhu (Autor:in)


    Erscheinungsdatum :

    22.11.2023


    Format / Umfang :

    380024 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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