KidneyChain: Leveraging Blockchain & Artificial Intelligence for a Streamlined Organ Donation Solution

Author:

Panda KapilORCID,Mazumder AnirudhORCID

Abstract

AbstractCurrently the kidney organ transplantation process is a manual and cumbersome process, resulting in organ wastage and reoccurring issues in patients due to a lack of organ health screening prior to transplantation. To solve these issues in the industry, we utilize blockchain technology and artificial intelligence to create a streamlined kidney transplantation process. Utilizing blockchain technology, we automated the organ matching process, and matched donors and patients based on the same metrics that UNOS clinicians use, resulting in efficient and faster matching. Furthermore, using artificial intelligence, we created a model with perfect accuracy that screens organs pre-transplantation to predict possible risk for common kidney diseases such as chronic kidney disease(CKD), acute kidney injury(AKI), and polycystic kidney disease(PKD), to prevent recurring issues in patients, post-transplantation. Furthermore, a tapped delay line convolutional neural network provides cybersecurity by identifying valid blockchain transactions from fake patterns with 100% accuracy, ensuring full data privacy. By synergizing blockchain, AI, and cybersecurity, this research creates an efficient, secure platform that could expand patient access to life-saving transplants, prevent transplant failures, and save thousands of lives currently lost due to inefficiencies and wait times.

Publisher

Cold Spring Harbor Laboratory

Reference11 articles.

1. Organ Donation Statistics. https://www.organdonor.gov/learn/organ-donation-statistics/, 2024. [Online; accessed 05-April-2008].

2. How we match organs. https://unos.org/transplant/how-we-match-organs/, 2024. [Online; accessed 04-April-2024].

3. Organ Procurement and Transplantation Network (OPTN) Modernization Initiative. https://www.hrsa.gov/optn-modernization/, 2024. [Online; accessed 04-March-2024].

4. A look into the future of blockchain technology

5. Ekblaw, A. ; Azaria, A. ; Halamka, J.D. ; Lippman, A. ; Vieira, T. A Case Study for Blockchain in Healthcare: “MedRec” prototype for electronic health records and medical research data White Paper MedRec: Using Blockchain for Medical Data Access and Permission Management IEEE Original Authors, 2016.

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