Blockchain Technology for Secure and Ethical AI‐Driven Healthcare

Abstract

The majority of the work now in publication discusses safeguard healthcare data however, the data modality—text, photos, audio, and sound—was not particularly addressed. Additionally, it was unclear how to safeguard while taking into account the differences in feature extraction depending on the input modalities. To determine the requirement for security, acoustic artificial intelligence (AI), the difficulty of assaults all examined. Based on research showing the unique technological characteristics of blockchains is developed. Fifteen research that highlighted blockchain's importance in protecting AI-driven healthcare systems were included in the review. Key findings showed how well blockchain works to improve diagnostic accuracy, data integrity, and decentralized data sharing (like federated learning [FL]). But issues like interoperability, scalability, and regulatory compliance kept coming up. The methodological quality was found to be moderate to high; however the quality evaluation also highlighted shortcomings in real-world validation and repeatability. But the discipline is still in its infancy, with major obstacles in the areas of ethical governance, technical standards, and scalability. Future research should place a high priority on interdisciplinary collaboration, clinical trials, and hybrid blockchain architectures.