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https://www.selleckchem.com/products/a-922500.html 68%, sensitivity of 68.55%, -score of 66.09%, and accuracy of 96.27%. Compared with existing works, our method significantly improves the performance of heartbeat classification. Our method is simple yet effective, which is potentially used for personal automatic heartbeat classification in remote medical monitoring. The source code is provided on https//github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification. Our method is simple yet effective, which is potentially used for personal automatic heartbeat classification in remote medical monitoring. The source code is provided on https//github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification. Application of Artificial Intelligence (AI) and the use of agent-based systems in the healthcare system have attracted various researchers to improve the efficiency and utility in the Electronic Health Records (EHR). Nowadays, one of the most important and creative developments is the integration of AI and Blockchain that is, Distributed Ledger Technology (DLT) to enable better and decentralized governance. Privacy and security is a critical piece in EHR implementation and/or adoption. Health records are updated every time a patient visits a doctor as they contain important information about the health and wellbeing of the patient and describes the history of care received during the past and to date. Therefore, such records are critical to research, hospitals, emergency rooms, healthcare laboratories, and even health insurance providers. In this article, a platform employing the AI and the use of multi-agent based systems along with the DLT technology for privacy preservation is proposed. The emphasis ofd systems backed by DLT technology for secure and effective handling EHR data. This proposed architecture uses various AI-based intelligent based agents and blockchain for providing privacy and security in EHR. Future enhancement in this work can b

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