Tuberculosis disease detection using blockchain in the healthcare system
by Atul Kumar Srivastava; Mitali Srivastava
International Journal of Healthcare Technology and Management (IJHTM), Vol. 19, No. 2, 2022

Abstract: Blockchain technology is being employed in a variety of disciplines, including online shopping, industry, medicine, and even government departments. The automated healthcare module is composed of two modules: one that oversees all functions and another that stores data in a central location. Tuberculosis is one of the fastest growing diseases, with an ever-increasing fatality rate all over the world. This research shows how a Blockchain-based system can be used to diagnose tuberculosis disease early using a machine learning algorithm, as well as keep track of patient data for monitoring and medication administration. The system given here can be utilised in the medical community to securely store, process, and communicate patient health data. Seven performance measuring matrices are used to evaluate the model: accuracy, sensitivity, specificity, precision, Matthew correlation coefficient (MCC), F1-score, and ROC. Experimental results show that, for these parameters, LR and KNN provide the best results.

Online publication date: Fri, 30-Sep-2022

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