Blockchain technology is a private, secure, trustworthy, and transparent information exchange performed in a decentralised manner. In this case, the coordination and validation efforts are simplified as the records are designed to update regularly and there is no difference in the two databases. This review focuses on how the blockchain addresses scalability challenges and provides solutions in the healthcare field through the implementation of blockchain technology. Accordingly, 16 solutions fell under two main areas, namely storage optimization and redesign of blockchain. However, limitations persist, including block size, high volume of data, transactions, number of nodes, and protocol challenges. This review consists of six stages, namely identification of research question, procedures of research, screening of relevant articles, keywording based on the abstract, data extraction, and mapping process. Through Atlas.ti software, the selected keywords were used to analyse through the relevant articles. As a result, 48 codes and 403 quotations were compiled. Manual coding was performed to categorise the quotations. The codes were then mapped onto the network as a mapping process. Notably, 16 solutions fell under two main areas, namely storage optimization and redesign of blockchain. Basically, there are 3 solutions compiled for storage optimization and 13 solutions for the redesign of the blockchain, namely blockchain modelling, read mechanism, write mechanism, and bi-directional network.
Disruptive technology, blockchain is propelling a technological intervention in healthcare due to its unique features and advantages. The healthcare industry is migrating to Health 4.0. Therefore, peer-to-peer (P2P) transactions in a decentralized and distributed manner make blockchain more lucrative to serve the needs of the healthcare industry of today. The revolutionary system blockchain has been discussed in the field of healthcare over the past five years. Hence, a systematic investigation of the existing body of knowledge concerning blockchain research in the healthcare domain is essential. The motivation of this study is to support further study based on the current research trend analysis through graphical visualization and analysis of the bibliographic material. Therefore, this study maps the expansion of scientific and academic research conducted concerning blockchain relevant to healthcare by utilizing a bibliometric analytic method to understand the state of the art. Bibliometric statistics have been utilized to analyze current scientific articles published in the Scopus database from 2016 to 2019. In addition, an overview of the publication trends over the first three months of 2020 has been undertaken to understand the research trend for the current year so far. The study serves the purpose of mapping research development trends in this area. The outcome discovered some beneficial insights such as the yearly trend of publications, top listed authors, institutes, countries and publishers from around the world. Moreover, this paper assists scholars to develop a theoretical framework to provide a primary source of reference in this field for further study of blockchain technology in the healthcare domain. INDEX TERMS Blockchain, bibliometric analysis, Health 4.0, healthcare, Scopus database.
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Digital medical images have become a vital resource that supports decision-making and treatment procedures in healthcare facilities. The medical image consumes large sizes of memory, and the size keeps on growth due to the trend of medical image technology. The technology of telemedicine encourages the medical practitioner to share the medical image to support knowledge sharing to diagnose and analyse the image. The healthcare system needs to ensure distributes the medical image accurately with zero loss of information, fast and secure. Image compression is beneficial in ensuring that achieve the goal of sharing this data. The region of interest-based hybrid medical compression algorithm plays the parts to reduce the image size and shorten the time of medical image compression process. Various studies have enhanced by combining numerous techniques to get an ideal result. This paper reviews the previous works conducted on a region of interest-based hybrid medical image compression algorithms.
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