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Bridging Gaps in Patient Care With AI-Driven IoMT: Intelligent Connectivity and Patient-Centric Results
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Author(s): Anita Mohanty (Silicon Institute of Technology, Silicon University, Bhubaneswar, India), Ambarish Gajendra Mohapatra (Silicon Institute of Technology, Silicon University, Bhubaneswar, India)and Subrat Kumar Mohanty (Einstein Academy of Technology and Management, Bhubaneswar, India)
Copyright: 2024
Pages: 16
Source title:
Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT)
Source Author(s)/Editor(s): Ahdi Hassan (Global Institute for Research Education and Scholarship, The Netherlands), Pronaya Bhattacharya (Amity University, Kolkata, India), Subrata Tikadar (Amity University, Kolkata, India), Pushan Kumar Dutta (Amity University, Kolkata, India)and Martin Sagayam (Karunya Institute of Technology and Sciences, India)
DOI: 10.4018/979-8-3693-2109-6.ch012
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Abstract
This chapter explores the integration of artificial intelligence (AI) within the internet of medical things (IoMT) to address significant challenges in contemporary healthcare. The focus is on communication barriers, data fragmentation, and resource allocation issues, advocating for AI-driven solutions such as federated learning, privacy-preserving techniques, and multi-party communications. Real-world case studies illustrate the tangible impact of AI on improving diagnosis, treatment, and patient engagement. Ethical considerations, challenges, and lessons learned provide a comprehensive understanding of the implementation landscape. Practical recommendations for implementation, including strategic frameworks and regulatory considerations, guide stakeholders in navigating this transformative journey. In summary, the chapter serves as a valuable resource for healthcare professionals, policymakers, and researchers, offering insights into the evolving landscape of patient care through AI-driven IoMT, to optimize healthcare delivery and address critical gaps in the healthcare system.
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