Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions

Shaikh, TA and Rasool, T and Verma, P (2023) Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions. In: Artificial Intelligence in Medicine, 146 .

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Abstract

Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networked system of medical equipment. It has been challenging to achieve high assurance in system software, interoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability due to the necessity to create complicated MCPS that are safe and efficient. The MCPS system is shown in the paper as a newly developed application case study of artificial intelligence in healthcare. Applications for various CPS-based healthcare systems are discussed, such as telehealthcare systems for managing chronic diseases (cardiovascular diseases, epilepsy, hearing loss, and respiratory diseases), supporting medication intake management, and tele-homecare systems. The goal of this study is to provide a thorough overview of the essential components of the MCPS from several angles, including design, methodology, and important enabling technologies, including sensor networks, the Internet of Things (IoT), cloud computing, and multi-agent systems. Additionally, some significant applications are investigated, such as smart cities, which are regarded as one of the key applications that will offer new services for industrial systems, transportation networks, energy distribution, monitoring of environmental changes, business and commerce applications, emergency response, and other social and recreational activities.The four levels of an MCPS's general architecture�data collecting, data aggregation, cloud processing, and action�are shown in this study. Different encryption techniques must be employed to ensure data privacy inside each layer due to the variations in hardware and communication capabilities of each layer. We compare established and new encryption techniques based on how well they support safe data exchange, secure computing, and secure storage. Our thorough experimental study of each method reveals that, although enabling innovative new features like secure sharing and safe computing, developing encryption approaches significantly increases computational and storage overhead. To increase the usability of newly developed encryption schemes in an MCPS and to provide a comprehensive list of tools and databases to assist other researchers, we provide a list of opportunities and challenges for incorporating machine intelligence-based MCPS in healthcare applications in our paper's conclusion. © 2023 Elsevier B.V.

Item Type:	Journal Article
Publication:	Artificial Intelligence in Medicine
Publisher:	Elsevier B.V.
Additional Information:	The copyright for this article belongs to Elsevier B.V..
Keywords:	Audition; Big data; Computer architecture; Cryptography; Cyber Physical System; Cybersecurity; Data acquisition; Data privacy; Digital storage; Diseases; Electronic data interchange; Embedded systems; Health care; Interoperability; Multi agent systems; Network architecture; Sensor networks, Context-Aware; CPS architecture; Dew computing; Encryption technique; High assurance; Machine intelligence; Medical cyber physical systems; Networked systems; Security and privacy; Systems architecture, Internet of things, artificial intelligence; cardiovascular disease; chronic disease; cloud computing; commercial phenomena; cybernetics; data aggregation; data base; data privacy; encryption; environmental change; epilepsy; health care system; hearing impairment; home care; human; internet of things; medical cyber physical system; respiratory tract disease; Review; taxonomy
Department/Centre:	Division of Interdisciplinary Sciences > Interdisciplinary Centre for Water Research
Date Deposited:	28 Feb 2024 11:57
Last Modified:	28 Feb 2024 11:57
URI:	https://eprints.iisc.ac.in/id/eprint/83645

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