Panacea: A Novel Architecture for Electronic Health Records System using Blockchain and Machine Learning | IEEE Conference Publication | IEEE Xplore

Panacea: A Novel Architecture for Electronic Health Records System using Blockchain and Machine Learning


Abstract:

In the information innovation unrest, electronic clinical records are a standard method for putting away patients' data in emergency clinics. Albeit some emergency clinic...Show More

Abstract:

In the information innovation unrest, electronic clinical records are a standard method for putting away patients' data in emergency clinics. Albeit some emergency clinic frameworks utilize server-based patient detail the board frameworks, they need a lot of capacity to store every one of the patients' clinical reports, in this manner influencing the versatility. Simultaneously, they are confronting a few troubles, for example, interoperability concerns, security and protection issues, digital as-saults to the concentrated stockpiling, and keeping up with sticking to clinical approaches. The proposed model is a private blockchain-based patient detail the board framework as most would consider to be normal to resolve the above issues. Arrangement proposes an appropriate secure record to grants effective framework access and frameworks recovery, which is secure and unchanging and man-made conscious’s fuelled instruments for clinical choice help. A better consensus system accomplishes the consensus of the information without huge energy use and organization congestion. Also, our model accomplishes high information security standards given a combination of crossbreed access control components, public-key cryptography, and a protected live ailment checking instrument. The proposed arrangement brings about effectively conveyed shrewd contracts according to the jobs of the framework, Ethereum based accreditation age and approval, Post Recovery Co-Morbidity Prediction, Disease Prediction Based on Symptoms, and Drug Recommendation gave Side Effects. The general goal of this arrangement is to bring the whole clinical industry into a common stage by utilizing a decentralized way to deal with a store, share clinical subtleties while disposing of the need to keep up with printed clinical records, and backing specialists utilizing exceptionally precise machine learning tools
Date of Conference: 21-22 April 2022
Date Added to IEEE Xplore: 01 July 2022
ISBN Information:
Conference Location: Bhilai, India

Contact IEEE to Subscribe

References

References is not available for this document.