Decentralized digital health ecosystems: a unified architecture for AI-enhanced medical record management

Traditional Electronic Health Record (EHR) systems suffer from critical vulnerabilities in security, interoperability, and patient data control. This paper introduces PolyMed, a novel decentralized platform designed to address these challenges. PolyMed combines blockchain, Artificial Intelligence (AI), and edge computing into a synergistic architecture. It uses the Polygon blockchain for immutable record-keeping and a Decentralized Autonomous Organization (DAO) for transparent governance. Patient identity is secured through privacy-preserving zero-knowledge proofs (ZKPs) and anchored to non-transferable Soulbound Tokens (SBTs), granting users true sovereignty over their data. The platform also includes a Decentralized Finance (DeFi) module to improve healthcare accessibility. Empirical evaluations on the Polygon Mainnet confirm the system's viability, showing sub-4-second transaction latencies and over 90% cost savings compared to legacy systems. The integrated AI model, leveraging a LightGBM classifier on a rich set of engineered features, achieves an Area Under the Curve (AUC) of <b>0.8543</b> and an accuracy of <b>80.33%</b> in emergency detection, demonstrating high reliability on a clinically relevant and imbalanced dataset. By aligning with global standards like General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA), PolyMed offers an integrated platform for patient-centric digital health management.

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Publication Details

Journal
Frontiers in Digital Health
Published
2025-10-27
DOI
https://doi.org/10.3389/fdgth.2025.1685628
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

Decentralized digital health ecosystems: a unified architecture for AI-enhanced medical record management

David Daniel, Praveen Joe I R, N. Saran, Preetham Venkatram C et al.
Frontiers in Digital Health
Blockchain Technology Applications and Security
article

Decentralized digital health ecosystems: a unified architecture for AI-enhanced medical record management

David Daniel, Praveen Joe I R, N. Saran, Preetham Venkatram C, Harsha Kumar A
article en

Abstract

Traditional Electronic Health Record (EHR) systems suffer from critical vulnerabilities in security, interoperability, and patient data control. This paper introduces PolyMed, a novel decentralized platform designed to address these challenges. PolyMed combines blockchain, Artificial Intelligence (AI), and edge computing into a synergistic architecture. It uses the Polygon blockchain for immutable record-keeping and a Decentralized Autonomous Organization (DAO) for transparent governance. Patient identity is secured through privacy-preserving zero-knowledge proofs (ZKPs) and anchored to non-transferable Soulbound Tokens (SBTs), granting users true sovereignty over their data. The platform also includes a Decentralized Finance (DeFi) module to improve healthcare accessibility. Empirical evaluations on the Polygon Mainnet confirm the system's viability, showing sub-4-second transaction latencies and over 90% cost savings compared to legacy systems. The integrated AI model, leveraging a LightGBM classifier on a rich set of engineered features, achieves an Area Under the Curve (AUC) of <b>0.8543</b> and an accuracy of <b>80.33%</b> in emergency detection, demonstrating high reliability on a clinically relevant and imbalanced dataset. By aligning with global standards like General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA), PolyMed offers an integrated platform for patient-centric digital health management.

Frontiers in Digital HealthVol. 7
Vellore Institute of Technology University (IN)
Openalex Percentile: Top 52%
Blockchain Technology Applications and Security
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Decentralized digital health ecosystems: a unified architecture for AI-enhanced medical record management — David Daniel, Praveen Joe I R, et al. · Frontiers in Digital Health (2025) | TGRS Research Map | TGRS