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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Ethics is a philosophical study of moral actions. Ethics attempts to determine what is valuable for individuals and society. It examines the rational justification of moral judgments and analyzes what is morally just, fair, and right. Bioethics is a sub-discipline of applied ethics that analyzes the philosophical, social, and legal issues in life sciences and medicine. Ethical theories serve as a foundation for decision-making and represent the viewpoints from which people seek direction. They...
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Updated: Jan 10, 2026

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Ethical AI in Healthcare: Integrating Zero-Knowledge Proofs and Smart Contracts for Transparent Data Governance.

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  • 1Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72388, Saudi Arabia.

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|November 27, 2025
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Summary

MediChainAI offers a secure framework for patient data ownership using Self-Sovereign Identity (SSI) and blockchain. This ensures privacy and controlled data sharing for AI/ML in healthcare.

Keywords:
MediChainAIMerkle treesSelf-Sovereign Identity (SSI)blockchainsmart contracts

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Area of Science:

  • Health Informatics
  • Cybersecurity
  • Artificial Intelligence

Background:

  • Integrating Artificial Intelligence (AI) and Machine Learning (ML) in healthcare promises improved patient care but faces challenges with confidential patient data security and privacy.
  • Current data handling practices raise concerns about data authenticity, security, and patient privacy, hindering the ethical development of AI/ML in medicine.

Purpose of the Study:

  • To introduce MediChainAI, a novel framework ensuring patient ownership and privacy of health data.
  • To enable secure and selective data sharing for AI/ML model training while maintaining data integrity and patient confidentiality.

Main Methods:

  • Integration of Self-Sovereign Identity (SSI) for patient data ownership.
  • Utilization of Blockchain technology for transparent and secure data management.
  • Implementation of Merkle trees for verified access to data subsets and smart contract-based encryption for controlled data access.

Main Results:

  • Patients gain full control over their health data, enabling selective sharing with providers and researchers.
  • The framework ensures data authenticity and privacy through cryptographic techniques and blockchain transparency.
  • MediChainAI facilitates the use of verified, legitimate data for training AI/ML models, enhancing diagnostic accuracy.

Conclusions:

  • MediChainAI provides a secure, patient-centric solution for managing health data in the era of AI/ML.
  • The framework addresses critical issues of data security, privacy, and authenticity, fostering ethical healthcare innovation.
  • This approach represents a significant advancement towards safer, more personalized, and trustworthy AI-driven healthcare solutions.