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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM58468
Volume:
10 |
3 |
Mar 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
— Moreover, the detection of diseases at early stages in an error free manner is considered significant in improving the healthcare sector. However, the existing intelligent systems are facing various problems like the accuracy of prediction for intelligent systems. Therefore, to improve the current intelligent systems, this paper proposes a novel intelligent system for medical disease detection using the blockchain approach. In this approach, the ensemble method is used in combination with the verification of medical data. Experimental analysis proves that the proposed machine learning approach attains accuracy of 83.50%, while deep learning achieves an accuracy of 75.00%. Moreover, the proposed blockchain-integrated intelligent disease detection using ensemble learning attains higher accuracy of 96.08%, precision of 0.94, recall of 0.95, and F1 score of 0.955.
KEYWORDS
Publication Date
3/29/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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