2023
DOI: 10.46481/jnsps.2023.992
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Secure Health Information System with Blockchain Technology

Abstract: This paper focuses on highlighting the problems that are associated with the absence of privacy and security of medical records in a healthcare system. It seeks to bridge the gap between the currently used security protocols in the management of health information, and encryption algorithms that should be used. Extant health information systems have always been developed with conventional databases. With all the privileges to read, write and execute assigned to the administrator, who has centralised control ov… Show more

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Cited by 14 publications
(15 citation statements)
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“…FS is a pre-processing step that reduces the dimensionality of a dataset by removing irrelevant and docile feats or parameters [6], [67] -leading to an improvement in the model classification performance [68]- [70]. It also yields streamlined data collection in model training for scenarios where cost is critical (e.g., target design in gene therapy).…”
Section: Feature Selection (Fs)mentioning
confidence: 99%
“…FS is a pre-processing step that reduces the dimensionality of a dataset by removing irrelevant and docile feats or parameters [6], [67] -leading to an improvement in the model classification performance [68]- [70]. It also yields streamlined data collection in model training for scenarios where cost is critical (e.g., target design in gene therapy).…”
Section: Feature Selection (Fs)mentioning
confidence: 99%
“…FS is a method to reduce dimensionality by removing irrelevant features or parameters [33], [34]. As a pre-processing step in machine learning tasks, FS has been successfully used in a variety of applications as its usefulness are numerous to include (and not limited to) overcoming the burden of parameter dimensionality and eliminating irrelevant cum docile features [35]- [37]; Thereby, leading to enhanced performance of the machine learning heuristics for both regression or classification task. FS becomes critical in domains where cost and the measure of attributes are of utmost importance.…”
Section: Feature Selection (Fs)mentioning
confidence: 99%
“…In this study, accuracy, recall, error rate (ER) and specificity are used to evaluate the performance of the detection models. The formulas of the above criteria are calculated as follows (Ibor et al, 2023;Ojugo, Aghware, et al, 2015b;Ojugo, Oyemade, et al, 2015). To measure effectiveness and accuracy, we measure their rate of misclassification and corresponding improvement percentages in both training and test data sets as summarized in Tables 3.…”
Section: Proposed Ensemble Evaluationmentioning
confidence: 99%