Advancing Healthcare: AI Integration, Interoperability and Sustainability Challenges
Main Article Content
Keywords
intelligent integration, artificial intelligence (AI), interoperable systems, healthcare, sustainability
Abstract
This article explores the evolving landscape of healthcare transformation through intelligent integration, focusing on artificial intelligence (AI), interoperability, and sustainability in the digital era. This analysis thoroughly investigates various aspects, including patient-centric immunization systems, blockchain-based e-health management, resource optimization, and adaptable clinical solutions. The investigation is framed around evolving healthcare considerations, emphasizing a thorough exploration of advancements, comparisons, and challenges encountered in the implementation of intelligent and integrated healthcare systems. The conclusion provides valuable insights for healthcare professionals and policymakers, guiding the development of a more connected and intelligent healthcare ecosystem.
References
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24. Shah C, Ibne Hossain NU, Khan MM, Alam ST. A dynamic Bayesian network model for resilience assessment in blockchain-based internet of medical things with time variation. Healthcare Analytics. 2023;4:100280. https://doi.org/10.1016/j.health.2023.100280.
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26. Javed I, Iqbal U, Bilal M, et al. Next Generation Infectious Diseases Monitoring Gages via Incremental Federated Learning: Current Trends and Future Possibilities. Computational Intelligence and Neuroscience. 2023;2023:1102715. https://doi.org/10.1155/2023/1102715.
27. Sumner J, Lim HW, Chong LS, et al. Artificial intelligence in physical rehabilitation: A systematic review. Artificial Intelligence in Medicine. 2023;146(2022):102693. https://doi.org/10.1016/j.artmed.2023.102693.
28. Huang C, Wang J, Wang S, Zhang Y. Internet of medical things: A systematic review. Neurocomputing. 2023;557:126719. https://doi.org/10.1016/j.neucom.2023.126719.
29. Ahmed SF, Bin Alam MS, Afrin S, et al. Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions. Information Fusion. 2024;102:102060. https://doi.org/10.1016/j.inffus.2023.102060.
30. Akhtar MN, Haleem A, Javaid M, Vasif M. Understanding Medical 4.0 implementation through enablers: An integrated multi-criteria decision-making approach. Informatics in Health. 2024;1(1):29‒39. https://doi.org/10.1016/j.infoh.2023.11.001.
31. Janbi N, Katib I, Mehmood R. Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture. Intelligent Systems with Applications. 2023;18:200231. https://doi.org/10.1016/j.iswa.2023.200231.
2. Taimoor N, Rehman S. Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey. IEEE Access. 2022;10:535‒563. https://doi.org/10.1109/ACCESS.2021.3137364.
3. Szczepaniuk H, Szczepaniuk EK. Cryptographic evidence-based cybersecurity for smart healthcare systems. Information Sciences. 2023;649:119633. https://doi.org/10.1016/j.ins.2023.119633.
4. Biswas S, Sharif K, Li F, Latif Z, Kanhere SS, Mohanty SP. Interoperability and Synchronization Management of Blockchain-Based Decentralized e-Health Systems. IEEE Transactions on Engineering Management. 2020;67(4):1363‒1376. https://doi.org/10.1109/TEM.2020.2989779.
5. Pimenta N, Chaves A, Sousa R, Abelha A, Peixoto H. Interoperability of Clinical Data through FHIR: A review. Procedia Computer Science. 2023;220:856-861. https://doi.org/10.1016/j.procs.2023.03.115.
6. Alshamrani M. IoT and artificial intelligence implementations for remote healthcare monitoring systems: A survey. Journal of King Saud University - Computer and Information Sciences. 2022;34(8):4687‒4701. https://doi.org/10.1016/j.jksuci.2021.06.005.
7. Boikanyo K, Zungeru AM, Sigweni B, Yahya A, Lebekwe C. Remote patient monitoring systems: Applications, architecture, and challenges. Scientific African. 2023;20. https://doi.org/10.1016/j.sciaf.2023.e01638.
8. Sowmitha R, Shanmuga RS, Harshini R, Arjuna S, Ram KC. Artificial Intelligence in Smart cities and Healthcare. EAI Endorsed Transactions on Smart Cities. 2022;6(3). https://doi.org/10.4108/eetsc.v6i3.2275.
9. Jang JS, Kim N, Lee SH. Scalable and Interoperable Platform for Precision Medicine: Cloud-based Hospital Information Systems. Healthcare Informatics Research. 2022;28(4):285‒286. https://doi.org/10.4258/hir.2022.28.4.285.
10. Madanian S, Nakarada-Kordic I, Reay S, Chetty T. Patients’ perspectives on digital health tools. PEC Innovation. 2023;2:100171. https://doi.org/10.1016/j.pecinn.2023.100171.
11. Atkinson KM, Mithani SS, Bell C, Rubens-Augustson T, Wilson K. The digital immunization system of the future: imagining a patient-centric, interoperable immunization information system. Therapeutic Advances in Vaccines and Immunotherapy. 2020;8:1‒15. https://doi.org/10.1177/2515135520967203.
12. Lim S, Rahmani R. Toward semantic IoT load inference attention management for facilitating healthcare and public health collaboration: A survey. Procedia Computer Science. 2020;177:371‒378. https://doi.org/10.1016/j.procs.2020.10.050.
13. Sciarretta E, Mancini R, Greco E. Artificial Intelligence for Healthcare and Social Services: Optimizing Resources and Promoting Sustainability. Sustainability. 2022;14(24):16464. https://doi.org/10.3390/su142416464.
14. Haleem A, Javaid M, Singh RP, Suman R. Medical 4.0 technologies for healthcare: Features, capabilities, and applications. Internet of Things and Cyber-Physical Systems. 2022;2:12‒30. https://doi.org/10.1016/j.iotcps.2022.04.001.
15. Reegu FA, Reeg L, Kumar V, et al. Interoperability Requirements for Blockchain-Enabled Electronic Health Records in Healthcare: A Systematic Review and Open Research Challenges. Security and Communication Networks. 2022;2022:9227343. https://doi.org/10.1155/2022/9227343.
16. Tariq N, Khan FA, Asim M. Security Challenges and Requirements for Smart Internet of Things Applications: A Comprehensive Analysis. Procedia Computer Science. 2021;191:425‒430. https://doi.org/10.1016/j.procs.2021.07.053.
17. Samuel G, Lucassen AM. The environmental sustainability of data-driven health research: A scoping review. Digital Health. 2022;8:20552076221111297. https://doi.org/10.1177/20552076221111297.
18. Richie C. Environmentally sustainable development and use of artificial intelligence in health care. Bioethics. 2022;36(5):547‒555. https://doi.org/10.1111/bioe.13018.
19. Alekseeva D, Ometov A, Arponen O, Lohan ES. The future of computing paradigms for medical and emergency applications. Computer Science Review. 2022;45:100494. https://doi.org/10.1016/j.cosrev.2022.100494.
20. Chen Z, Wu M, Chan A, Li X, Ong YS. Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges [Review Article]. IEEE Computational Intelligence Magazine. 2023;18(2):60‒77. https://doi.org/10.1109/MCI.2023.3245733.
21. Singh R, Gill SS. Edge AI: A survey. Internet of Things and Cyber-Physical Systems. 2023;3:71‒92. https://doi.org/10.1016/j.iotcps.2023.02.004.
22. Martínez I, González F. Wireless standard-compliant e-health solution for elderly people with multiuser identification. Heliyon. 2023;9(4). https://doi.org/10.1016/j.heliyon.2023.e15394.
23. Uppal S, Kansekar B, Mini S, Tosh D. HealthDote: A blockchain-based model for continuous health monitoring using interplanetary file system. Healthcare Analytics. 2023;3:100175. https://doi.org/10.1016/j.health.2023.100175.
24. Shah C, Ibne Hossain NU, Khan MM, Alam ST. A dynamic Bayesian network model for resilience assessment in blockchain-based internet of medical things with time variation. Healthcare Analytics. 2023;4:100280. https://doi.org/10.1016/j.health.2023.100280.
25. Ahmad R, Hämäläinen M, Wazirali R, Abu-Ain T. Digital-care in next generation networks: Requirements and future directions. Computer Networks. 2023;224:109599. https://doi.org/10.1016/j.comnet.2023.109599.
26. Javed I, Iqbal U, Bilal M, et al. Next Generation Infectious Diseases Monitoring Gages via Incremental Federated Learning: Current Trends and Future Possibilities. Computational Intelligence and Neuroscience. 2023;2023:1102715. https://doi.org/10.1155/2023/1102715.
27. Sumner J, Lim HW, Chong LS, et al. Artificial intelligence in physical rehabilitation: A systematic review. Artificial Intelligence in Medicine. 2023;146(2022):102693. https://doi.org/10.1016/j.artmed.2023.102693.
28. Huang C, Wang J, Wang S, Zhang Y. Internet of medical things: A systematic review. Neurocomputing. 2023;557:126719. https://doi.org/10.1016/j.neucom.2023.126719.
29. Ahmed SF, Bin Alam MS, Afrin S, et al. Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions. Information Fusion. 2024;102:102060. https://doi.org/10.1016/j.inffus.2023.102060.
30. Akhtar MN, Haleem A, Javaid M, Vasif M. Understanding Medical 4.0 implementation through enablers: An integrated multi-criteria decision-making approach. Informatics in Health. 2024;1(1):29‒39. https://doi.org/10.1016/j.infoh.2023.11.001.
31. Janbi N, Katib I, Mehmood R. Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture. Intelligent Systems with Applications. 2023;18:200231. https://doi.org/10.1016/j.iswa.2023.200231.
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Nov 18, 2024
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How to Cite
Advancing Healthcare: AI Integration, Interoperability and Sustainability Challenges. (2024). Journal of Applied Interdisciplinary Research, Special Issue, 64-74. https://doi.org/10.25929/j3xxxy63