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  • Open Access

    ARTICLE

    Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

    Jingjing Nie1,*, Zhenhua Chen2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4763-4779, 2024, DOI:10.32604/cmc.2024.051181 - 20 June 2024

    Abstract The Internet of Medical Things (IoMT) is an application of the Internet of Things (IoT) in the medical field. It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems, which is essential in smart healthcare. However, Personal Health Records (PHRs) are normally kept in public cloud servers controlled by IoMT service providers, so privacy and security incidents may be frequent. Fortunately, Searchable Encryption (SE), which can be used to execute queries on encrypted data, can address the issue above. Nevertheless, most existing SE schemes cannot solve the vector dominance threshold… More >

  • Open Access

    ARTICLE

    A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

    Kirupa Shankar Komathi Maathavan1,*, Santhi Venkatraman2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 765-779, 2022, DOI:10.32604/iasc.2022.022276 - 17 November 2021

    Abstract The major operation of the blood bank supply chain is to estimate the demand, perform inventory management and distribute adequate blood for the needs. The proliferation of big data in the blood bank supply chain and data management needs an intelligent, automated system to classify the essential data so that the requests can be handled easily with less human intervention. Big data in the blood bank domain refers to the collection, organization, and analysis of large volumes of data to obtain useful information. For this purpose, in this research work we have employed machine learning… More >

  • Open Access

    ARTICLE

    Machine Learning Techniques Applied to Electronic Healthcare Records to Predict Cancer Patient Survivability

    Ornela Bardhi1,2,*, Begonya Garcia Zapirain1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326 - 13 April 2021

    Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178… More >

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