Background: Interoperability, privacy, and the background of healthcare information are significant issues in the healthcare industry, mainly because of the fragmentation of the data. Conventional solutions are not secure, transparent, and accurate enough to share data effectively. Purpose: The purpose of the study is to examine how blockchain and Artificial Intelligence (AI) may be integrated to streamline the process of sharing healthcare data to be secure, intact, and provide superior decision-making in clinical practice. Methods: The study will be based on the use of blockchain and AI in healthcare, namely, using Smart Contracts to share electronic health records, Federated Learning to train AI models, and identity access control by AI using blockchain systems. The models have been tested on benchmark healthcare data, and parameters of the models, which include the data access latency, transactions per second, and the accuracy of prediction. Findings: The AI-blockchain hybrid architecture was shown to have a considerable enhancement in the workability of healthcare information, the stability of the system, and the correctness of choices. The prediction models based on AI worked successfully in identifying medical anomalies and analyzing various medical data. Also, blockchain provides integrity of data because of a decentralized and unalterable ledger. Conclusion: The paper identifies the possibility of blockchain and AI integration in health to implement the exchange of data. The proposed system is expected to increase security, decrease the latency, and increase the accuracy of the prediction, which is a promising solution to secure, efficient, and reliable data exchange in healthcare.
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