Blockchain for Healthcare Medical Records Management System with Sharing Control

• Main Authors: Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Zabidi, Suriza Ahmad
• Format: Conference Proceeding
• Language: English
• Subjects: Blockchain; Blockchains; Control systems; Convolutional neural networks; healthcare data; Machine Learning; Machine learning algorithms; management; Medical services; Reliability; Semantics
• ISSN: 2640-6535
• DOI: 10.1109/ICSIMA50015.2021.9526301

Nowadays, with large quantities of data in every industry and the advancement of technology, solutions to a wide range of problems can be resolved. In this paper, Machine Learning and Blockchain are used to propose a solution to difficulties linked to healthcare data management systems. Machine Learning allows the extraction of needed-only information that is relevant from data. This is achieved using trained algorithms that provide an intelligent decision strategy based on Convolutional Neural Networks (CNN) to automatically extract high-level semantic information from electronic medical records and then perform automatic diagnosis. Once medical data is saved, the next issue is data sharing and reliability. This is where Blockchain technology comes into play. The Blockchain with consensus protocol ensures that information is authentic, and transactions are safe. By putting the patient at the center of the healthcare system and boosting the privacy and interoperability of health data, this proposed solution can improve health care administration. This paper focuses on using Blockchain technology to solve healthcare data management problems while also incorporating some essential Machine Learning features. The expected result of the proposed system 98.67% accuracy and 96.02% recall, demonstrating that employing a convolutional neural network to learn high-level semantic aspects of electronic medical records and then undertake assist diagnosis is feasible and valuable.