Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective

Rathore, Nitin; Gupta, Rajesh; Thakkar, Nihar; Gohil, Keyaba; Tanwar, Sudeep; Aujla, Gagangeet Singh; Alqahtani, Fayez; Tolba, Amr

Abstract

This paper explores artificial intelligence (AI) and edge–fog interplay to strengthen healthcare informatics (HCI), while also considering the blockchain perspective for securing HCI to transform cloud-based HCI to edge–fog-based HCI to serve real-time responses for critical healthcare applications. This article discusses that AI is vital in providing better healthcare, precision medicine, and personalized treatments. A comprehensive review of edge–fog interplay-based HCI and blockchain-based HCI demonstrated the need for integrating blockchain and edge–fog interplay for successful HCI. Subsequently, some current research projects explore edge computing, fog computing, and blockchain in the healthcare sector to securely store and share patient data, thereby providing real-time data analysis, which is also highlighted. The latter part reflects some essential aspects of blockchain in healthcare, such as immutability, trustworthiness, and traceability. We also present a case study on AI-edge–fog interplay, and blockchain on heart stroke prediction for HCI that examines the practical application of the amalgamation of such technologies required to refine the healthcare sector to support the proposed analysis. Finally, this work discusses the future challenges of integrating AI, edge–fog interplay, and blockchain in the field of HCI.

Citation

Rathore, N., Gupta, R., Thakkar, N., Gohil, K., Tanwar, S., Aujla, G. S., Alqahtani, F., & Tolba, A. (2024). Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective. Ad Hoc Networks, 169, Article 103727. https://doi.org/10.1016/j.adhoc.2024.103727

• Journal Article Type: Article
• Acceptance Date: Nov 20, 2024
• Online Publication Date: Dec 4, 2024
• Publication Date: Dec 7, 2024
• Deposit Date: Dec 16, 2024
• Journal: Ad Hoc Networks
• Print ISSN: 1570-8705
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 169
• Article Number: 103727
• DOI: https://doi.org/10.1016/j.adhoc.2024.103727
• Public URL: https://durham-repository.worktribe.com/output/3217244