Blockchain-based Healthcare Records with Heart Disease Prediction

Author(s)	Mr. sushanth das, Mr. venkat narayana reddy, Mr. R sai Kalyan, Dr.Diwakar R
Country	India
Abstract	Clinics and small health centers in resource-limited areas often lack both reliable record-keeping and tools to support clinical decisions across several conditions [1], [6]. We built MediLedger to tackle this: it ties together hardware for capturing electrocardiogram (ECG) and related clinical data [4], [5], [12], trained models that predict multiple diseases [9], [10], [11], and storage of health records on a blockchain so entries stay auditable and tamper-resistant [2], [7], [8]. The setup targets primary care. It runs predictions for diabetes, heart, kidney, and liver disease, keeps results in a local SQLite database, and can push verified entries onto an Ethereum- style chain [13] through smart contracts. Here we cover the ECG hardware (Arduino Nano with an AD8232 module), the path from raw sensor data to blockchain, and the software side—data flow, use cases, sequences, and component/deployment views. MediLedger shows that combining cheap sensing, ML-based prediction, and blockchain for health records is workable in a primary- care setting
Keywords	Blockchain, healthcare records, primary healthcare, multi-disease prediction, ECG, Arduino, AD8232, smart contracts, machine learning, Ethereum
Field	Engineering
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-17

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