The healthcare sector has benefited greatly from the integration of AI/ML with distributed technologies like edge computing, blockchain, and Internet of Things (IoT) to address challenges like data interoperability, security, and scalability. This synergy has a major impact on patient care, medical research, and the efficiency of the healthcare system. AI/ML techniques are used in a variety of fields, including drug development, medical imaging interpretation, picture identification, predictive analytics, and sickness prediction. The relationship between AI/ML and distributed technologies—such as decentralized architectures for safe access to real-time data sources, blockchain for data integrity and privacy, and edge computing for low-latency processing—is discussed. When combining AI/ML with dispersed technology, the healthcare business faces trends and concerns related to interoperability, legal compliance, and ethical issues.
Authors: B. Gopi, M. L. Sworna Kokila, Christopher V. Bibin, D. Sasikala, Eric Howard, Sampath Boopathi
DOI: https://doi.org/10.4018/979-8-3693-2569-8.ch019
Publish Year: 2024
