SURVEY ARTICLE
Transforming Healthcare With Artificial Intelligence and Blockchain: A Secure, Transparent and Energy-Efficient Approach
Sagnik Datta,
Suyel Namasudra,
Nageswara Rao Moparthi,
Suchi Kumari,
Ruben Gonzalez Crespo,
Sagnik Datta
Department of Computer Science and Engineering, National Institute of Technology Agartala, Agartala, India
Amrita Vishwa Vidyapeetham, Amrita School of Computing, Agartala, India
Search for more papers by this authorSuyel Namasudra
Department of Computer Science and Engineering, National Institute of Technology Agartala, Agartala, India
Search for more papers by this authorCorresponding Author
Nageswara Rao Moparthi
Amrita Vishwa Vidyapeetham, Amrita School of Computing, Agartala, India
Correspondence:
Nageswara Rao Moparthi ([email protected])
Ruben Gonzalez Crespo ([email protected])
Search for more papers by this authorSuchi Kumari
Department of Computer Science and Engineering, Shiv Nadar Institute of Eminence, Delhi NCR, India
Search for more papers by this authorCorresponding Author
Ruben Gonzalez Crespo
Department of Computer Science and Technology, Universidad Internacional de La Rioja, Logroño, La Rioja, Spain
Correspondence:
Nageswara Rao Moparthi ([email protected])
Ruben Gonzalez Crespo ([email protected])
Search for more papers by this authorSagnik Datta,
Suyel Namasudra,
Nageswara Rao Moparthi,
Suchi Kumari,
Ruben Gonzalez Crespo,
Sagnik Datta
Department of Computer Science and Engineering, National Institute of Technology Agartala, Agartala, India
Amrita Vishwa Vidyapeetham, Amrita School of Computing, Agartala, India
Search for more papers by this authorSuyel Namasudra
Department of Computer Science and Engineering, National Institute of Technology Agartala, Agartala, India
Search for more papers by this authorCorresponding Author
Nageswara Rao Moparthi
Amrita Vishwa Vidyapeetham, Amrita School of Computing, Agartala, India
Correspondence:
Nageswara Rao Moparthi ([email protected])
Ruben Gonzalez Crespo ([email protected])
Search for more papers by this authorSuchi Kumari
Department of Computer Science and Engineering, Shiv Nadar Institute of Eminence, Delhi NCR, India
Search for more papers by this authorCorresponding Author
Ruben Gonzalez Crespo
Department of Computer Science and Technology, Universidad Internacional de La Rioja, Logroño, La Rioja, Spain
Correspondence:
Nageswara Rao Moparthi ([email protected])
Ruben Gonzalez Crespo ([email protected])
Search for more papers by this authorFirst published: 12 July 2025
ABSTRACT
The healthcare industry is undergoing a transformative shift with the integration of blockchain technology and Artificial Intelligence (AI). Traditional healthcare systems struggle with data security, lack of transparency, and inefficiencies in resource allocation, leading to increased risks and operational challenges. AI-driven models provide intelligent solutions by enabling predictive diagnostics, fraud detection, and personalised treatment plans, while blockchain ensures data integrity, security, and decentralised access control. The synergy between AI and blockchain enhances decision-making, optimises resource utilisation and fosters trust in healthcare systems by automating processes with greater transparency and security. AI-powered analytics can extract meaningful insights from vast healthcare datasets, improving patient outcomes and streamlining supply chains. Meanwhile, blockchain's immutable ledger safeguards medical data, preventing breaches and ensuring regulatory compliance. This paper presents a comprehensive review of blockchain solutions in healthcare, exploring their impact on enhancing security, promoting transparency and improving energy efficiency. Additionally, this paper also presents insights on the integration of AI and blockchain in healthcare. It categorises existing blockchain-based frameworks and highlights emerging trends, challenges, and future research directions. This review aims to serve as a foundational reference for researchers and practitioners developing secure, transparent, and intelligent healthcare systems.
Open Research
Data Availability Statement
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
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