AI-Enabled Medical Devices for Precision Immunology
DOI:
https://doi.org/10.61424/kcm7ph10Keywords:
Artificial intelligence; AI-enabled medical devices; Precision immunology; Precision medicine; Immunotherapy; Multi-omics; Wearable biosensors; Personalized healthcareAbstract
AI-enabled medical devices are revolutionizing precision immunology through enabling personalized strategies for diagnosis, monitoring, and treatment of immune-mediated diseases. The integration of AI with medical technologies has emerged as a convergence of breakthrough capability to combine clinical, immunological, genomic, multi-omic, and real-time physiological signals, offering unprecedented opportunities to enhance disease stratification, anticipate treatment response, and tailor individualized healthcare. This review summarizes recent progress in AI-enabled medical devices and their broadening applications in precision immunology as leveraging tumor immunology, autoimmune diseases, allergic conditions, infectious diseases, cardiovascular immunology, lupus nephritis, rheumatoid arthritis, sepsis, and more. The review further discusses the enablement of precision medicine by integration of wearable biosensors, intelligent diagnostic platforms, connected health systems, adaptive therapeutic devices, and multi-omic analytics. Additionally, the review addresses current barriers to clinical translatability of these technologies including data acquisition quality and standardization, system interoperability, algorithm transparency, regulatory oversight, cybersecurity, and ethical concerns. We also highlight future innovations including intelligent biosensors, explainable immuno-AI, adaptive responsive drug delivery systems, and connected digital health systems.
References
Adenike, A. (2025). Artificial Intelligence (AI)-Driven Fraud Detection in Commercial Banking: Outcomes From Central Bank Of Nigeria (CBN) Regulatory Sandbox in Global Fintech Context Including Us Federal Reserve Pilots. Stout in Business and Management, 1(1), 80-89. https://doi.org/10.61424/5ff9ce53
Afzal, M., Sah, A. K., Agarwal, S., Tanzeel, A., Elshaikh, R. H., Alobeidli, F. A., ... & Choudhary, A. (2024). Advancements in the treatment of autoimmune diseases: Integrating artificial intelligence for personalized medicine. Trends in Immunotherapy, 8(2).
Ali, K. A., Choudhuri, S., Chakraborty, R., Pradhan, A., Kotal, A., & Shaharyar, M. A. (2025). AI technology-powered precision medicine and smart healthcare: Technical advancements and prospects. In AI and precision medicine in infectious disease management (pp. 51–70). CRC Press.
Alshorman, J., Mehran, M. J., Bahrami, Y., Mohammadzadeh, S., Barzigar, R., Morshedi, M., ... & Wang, Y. (2026). Artificial intelligence in immunotherapy: Revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases. Clinical and Experimental Medicine, 26(1), 185.
Atsaves, V., Lekakis, L., Feretzaki, M., Leventaki, V., Liakou, C., Drakos, E. & others, 2009. JunB oncogenic activity in anaplastic large cell lymphoma. Laboratory Investigation, 89, p.254A.
Chao, C. C., Chiu, Y., Yeung, L., Yee, C., Jiang, C., & Shen, X. (2025). AI/ML-empowered approaches for predicting T cell-mediated immunity and beyond. Frontiers in Immunology, 16, 1651533.
Chao, C. C., Chiu, Y., Yeung, L., Yee, C., Jiang, C., & Shen, X. (2025). AI/ML-empowered approaches for predicting T cell-mediated immunity and beyond. Frontiers in Immunology, 16, 1651533.
Chen, Y. M., Hsiao, T. H., Lin, C. H., & Fann, Y. C. (2025). Unlocking precision medicine: Clinical applications of integrating health records, genetics, and immunology through artificial intelligence. Journal of Biomedical Science, 32(1), 16.
Derraz, B., Breda, G., Kaempf, C., Baenke, F., Cotte, F., Reiche, K., ... & Gilbert, S. (2024). New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology. NPJ Precision Oncology, 8(1), 23.
Dinc, R., & Ardic, N. (2026). Immunologically adaptive endovascular devices: Integrating thrombo-inflammation, biomaterials design, and artificial intelligence for precision cardiovascular intervention. International Journal of Molecular Sciences, 27(8), 3493.
Gogali, F., Paterakis, G., Rasidakis, G., Kaltsas, G., Gousis, P., Neonakis, E. & others, 2011. T regulatory lymphocytes (Tregs) and NK cell interaction in thyroid papillary cancer (PTC): immunotherapy perspectives. Basic & Clinical Pharmacology & Toxicology, 109, p.29.
Kitonakis, N. & Kontis, A., 2008. The determinants of Greek foreign direct investments in Southeast European countries. Southeast European and Black Sea Studies, Taylor & Francis.
Konstantinou, G. N., Anderson III, W. C., Bagkis, E., Brown, Z., Karatzas, K., Kassandros, T., ... & Nyenhuis, S. M. (2025). AI-driven wearable and connected technology for allergy: Real-time monitoring and predictive management for personalized care. The Journal of Allergy and Clinical Immunology: In Practice.
Liakou, A.I., Arabatzi, K., Liakou, C.I. & Theodorakis, M.J. (2008) ‘Impact of obesity on cytokine secretion patterns following an oral glucose tolerance test in individuals with normal glucose tolerance’, Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Liakou, A.I., Arabatzi, K., Liakou, C.I. & Theodorakis, M.J., 2008. Impact of obesity on cytokine secretion patterns following an oral glucose tolerance test in individuals with normal glucose tolerance. Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Liakou, A.I., Liakou, C.I. & Zouboulis, C.C., 2012. Acne and nutrition. Handbook of Diet, Nutrition and the Skin, pp.413-422.
Liakou, C.I. and Plytas, M. (2025) ‘Patient access to high-risk devices for unmet medical needs’, International Journal of Engineering Technology and Research Management, 9(3), pp. 41–46. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741357556-MAR06.pdf.
Liakou, C.I., Papadakis, M. and Plytas, M. (2025) ‘Clinical evaluation of immunotherapy vaccines as medical devices: Regulatory challenges and assessment strategies’, International Journal of Engineering Technology and Research Management, 9(3), pp. 32–31. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741355709-MAR04.pdf.
Liakou, C.I., Papadakis, M. and Plytas, M. (2025) ‘The challenges for manufacturers of the increased clinical evaluation requirements under the European Union medical device regulations’, International Journal of Engineering Technology and Research Management, 9(3), pp. 32–40. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741356854-MAR05.pdf.
Mane, D. V., Deshmukh, A. N., Ambare, R. H., Solankar, A. A., & Madane, C. S. (2024). AI in autoimmune diseases: Transforming diagnosis and treatment. Journal of Pharmaceutical and Biological Sciences, 12(2), 109–118.
Mane, D. V., Deshmukh, A. N., Ambare, R. H., Solankar, A. A., & Madane, C. S. (2024). AI in autoimmune diseases: Transforming diagnosis and treatment. Journal of Pharmaceutical and Biological Sciences, 12(2), 109–118.
Negut, I., & Visan, A. I. (2025). AI-enhanced diagnosis for immunological disorders. In AI-assisted computational approaches for immunological disorders (pp. 63–106). IGI Global Scientific Publishing.
Prema, S. S., Ganapathy, D., & Shanmugamprema, D. (2026). AI-driven epidemiology: The next frontier in precision public health. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 16(2), e70077.
Qoronfleh, M. W. (2026). Precision medicine in medical technology-medtech: The future of healthcare through personalized devices. Health and Technology, 16(3), 539–545.
Sah, A. K., Elshaikh, R. H., Shalabi, M. G., Abbas, A. M., Prabhakar, P. K., Babker, A. M., ... & Agarwal, S. (2025). Role of artificial intelligence and personalized medicine in enhancing HIV management and treatment outcomes. Life, 15(5), 745.
Sergeevna, K. T. (2022). Dynamic valuation models for tokenized economies. Актуальные исследования, 42.
Shang, S., Xia, J., He, G., Zheng, Y., Zhang, J., Lu, H., ... & Chen, X. (2025). Advances in precision medicine for lupus nephritis: Biomarker- and AI-driven diagnosis and treatment response prediction and targeted therapies. EBioMedicine, 117.
Sharma, P., Liakou, C., Kamat, A., Chen, H., Ng Tang, D., Sun, J., Troncoso, P. & others, 2008. Immunological impact of anti-CTLA4 therapy in a neoadjuvant setting. Cancer Immunity, 8(Suppl_1).
Sharma, P., Liakou, C., Kamat, A., Chen, H., Ng Tang, D., Sun, J., Troncoso, P., et al. (2008) ‘Immunological impact of anti-CTLA4 therapy in a neoadjuvant setting’, Cancer Immunity, 8(Suppl_1).
Sharma, P., Liakou, C., Kamat, A., Tang, D.N., Chen, H., Sun, J., Troncoso, P. & others, 2008. CTLA-4 blockade increases interferon-gamma-producing CD4 (+) ICOS (HI) cells to shift the ratio of effector to regulatory T cells in cancer patients. Journal of Immunotherapy, 31(9), p.960.
Shen, Y., Zhang, P., Luo, J., Chen, S., Gu, S., Lin, Z., & Tang, Z. (2026). Artificial intelligence drives advances in multi-omics analysis and precision medicine for sepsis. Biomedicines, 14(2), 261.
Sideris, A.C., Tsakiris, S., Messari, I., Liakou, C.I. & Carageorgiou, H. (2008) Effects of rivastigmine plus selegiline [(-) deprenyl)] on brain enzymes, antioxidant status and learning performance of aged rats, Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Sklavounos, D., Edoh, A. & Plytas, M., 2017. A statistical approach based on EWMA and CUSUM control charts for R2L intrusion detection. 2017 Cybersecurity and Cyberforensics Conference (CCC), pp.25-30.
Thakur, G., Bassi, P., Singh, T. G., Tamilanban, T., Dhanasekaran, S., Singh, S. K., ... & Subramaniyan, V. (2026). Precision therapeutics in rheumatoid arthritis: Emerging strategies in active, stimuli-responsive, and AI-enabled drug delivery. SN Comprehensive Clinical Medicine, 8(1), 169.
Tzamaria, M., Liakou, C. & Papadakis, M. (2025) ‘CTLA-4 Treatment in Pancreatic Cancer’, International Journal of Advanced Research in Engineering, Science & Management, 13(3), pp. 2826-2833. Available at: https://www.ijaresm.com/volume-13/issue-3-march-2025.
van Breugel, M., Greenhawt, M., Eguiluz-Gracia, I., Jaen, M. J. T., Anagnostou, A., & Koppelman, G. H. (2025). Artificial intelligence in allergy and immunology: Recent developments, implementation challenges, and the road towards clinical impact. Journal of Allergy and Clinical Immunology.
Wang, F., Lim, P., Koh-lionel, L., & Smirnova, M. (n.d.). AI-driven precision medicine: Shaping the future of personalized healthcare.
Zapotoczny, G., Goyal, A., Christmas, M., Qazi, S., Carroll, M., & Espinoza, J. (2026). FDA-regulated AI-enabled medical devices with pediatric indications. JAMA Network Open, 9(3), e262636.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Chrysoula I. Liakou, Marios Papadakis, Markos Plytas (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
