Volume 1 Number 1 2025
Integrative approaches of AI in personalised disease management: From diagnosis to drug delivery
Md Sakil Amin1*, Azizur Rahman2
Paradise 1 (1) 1-10 https://doi.org/10.25163/paradise.1110339
Submitted: 29 June 2025 Revised: 31 August 2025 Published: 02 September 2025
Abstract
Artificial Intelligence (AI) is transforming healthcare in remarkable ways, enabling more precise, data-driven, and personalised approaches to managing diseases. In the realm of personalised medicine, AI is reshaping the entire journey of patient care, from early diagnosis and risk assessment to creating customised treatment plans and developing targeted drug delivery systems. These advancements have become possible due to the merging of vast medical data, computational modelling, and cutting-edge machine learning algorithms. This paper explores how AI enhances personalised disease management by integrating various technologies across multiple fields, including medical imaging, genomic data analysis, predictive analytics, and clinical decision support systems. AI's capability to analyse medical images and decode genetic information enables early and accurate disease detection, along with tailored therapeutic strategies for patients. Moreover, AI-driven tools help optimise treatment pathways, adjust drug regimens, and support integrative medicine by blending conventional and complementary therapies. Beyond its clinical applications, AI also streamlines administrative tasks, making healthcare workflows more efficient. However, as we integrate AI into healthcare, we must also consider critical ethical issues, including data privacy, algorithmic bias, transparency, and the need for explainable decision-making in clinical environments. The paper concludes with a forward-looking perspective on future innovations, such as AI-enabled gene editing, virtual health assistants, and quantum computing for drug discovery. As we move forward, ensuring that AI's implementation is equitable, secure, and ethically sound will be crucial for unlocking its full potential in delivering genuinely personalised healthcare solutions.
Keywords: Artificial Intelligence, Personalized Healthcare, Workflow Optimization, Automation, Patient-Centred Care
References
Abdelhalim, H., Berber, A., Lodi, M., Jain, R., Nair, A., Pappu, A., Patel, K., Venkat, V., Venkatesan, C., Wable, R., Dinatale, M., Fu, A., Iyer, V., Kalove, I., Kleyman, M., Koutsoutis, J., Menna, D., Paliwal, M., Patel, N., … Ahmed, Z. (2022). Artificial intelligence, healthcare, clinical genomics, and pharmacogenomics approaches in precision medicine. Frontiers in Genetics, 13. https://doi.org/10.3389/fgene.2022.929736
Akter, L., Mondal, R. S., Bhuiyan, M. N. A. (2025). "Artificial Intelligence Application in Public Health: Advancement and Associated Challenges", Journal of Primeasia, 6(1),1-10,10325 https://doi.org/10.25163/primeasia.6110325
Ali, J., Jusoh, A., Idris, N., Airij, A. G., & Chandio, R. (2022). Wearable devices in healthcare services. Bibliometrix analysis by using the R package. International Journal of Online and Biomedical Engineering, 18(8). https://doi.org/10.3991/ijoe.v18i08.31785
Amboree, T. L., Montealegre, J. R., Fujimoto, K., Mgbere, O., Darkoh, C., & Wermuth, P. P. (2022). Exploring preventive healthcare in a high-risk, vulnerable population. International Journal of Environmental Research and Public Health, 19(8). https://doi.org/10.3390/ijerph19084502
Batarseh, F. A., Ghassib, I., Chong, D., & Su, P. H. (2020). Preventive healthcare policies in the US: Solutions for disease management using big data analytics. Journal of Big Data, 7(1). https://doi.org/10.1186/s40537-020-00315-8
Bhuiyan, M. N. A., Mondal, R. S., Akter, L. (2025). "Advancing Cancer Imaging with Artificial Intelligence Clinical Application and Challenges", Journal of Primeasia, 6(1),1-11,10322
https://doi.org/10.25163/primeasia.6110322
Bhuiyan, M. N. A., & Mondal, R. S. (2023). AI-Driven Predictive Analytics in Healthcare: Evaluating Impact on Cost and Efficiency. Journal of Computational Analysis and Applications, 31(4).
Blasiak, A., Khong, J., & Kee, T. (2020). CURATE.AI: Optimising personalised medicine with artificial intelligence. SLAS Technology, 25(2). https://doi.org/10.1177/2472630319890316
Brady, A. P., & Neri, E. (2020). Artificial intelligence in radiology—ethical considerations. Diagnostics, 10(4). https://doi.org/10.3390/diagnostics10040231
Cesario, A., D’oria, M., Bove, F., Privitera, G., Boškoski, I., Pedicino, D., Boldrini, L., Erra, C., Loreti, C., Liuzzo, G., Crea, F., Armuzzi, A., Gasbarrini, A., Calabresi, P., Padua, L., Costamagna, G., Antonelli, M., Valentini, V., Auffray, C., & Scambia, G. (2021). Personalised clinical phenotyping through systems medicine and artificial intelligence. Journal of Personalised Medicine, 11(4). https://doi.org/10.3390/jpm11040265
Chavarriaga, J., & Moreno, C. (2020). Precision medicine, artificial intelligence, and genomic markers in urology: Do we need to tailor our clinical practice? Urologia Colombiana, 29(3). https://doi.org/10.1055/s-0040-1714148
Davenport, T., & Kalakota, R. (2019). The Potential for Artificial Intelligence in Healthcare Future Healthcare Journal, 6(2). https://doi.org/10.7861/futurehosp.6-2-94
Fritsch, S. J., Blankenheim, A., Wahl, A., Hetfeld, P., Maassen, O., Deffge, S., Kunze, J., Rossaint, R., Riedel, M., Marx, G., & Bickenbach, J. (2022). Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. Digital Health, 8. https://doi.org/10.1177/20552076221116772
Gokdeniz, S. T., & Kamburoglu, K. (2022). Artificial intelligence in dentomaxillofacial radiology. World Journal of Radiology, 14(3). https://doi.org/10.4329/wjr.v14.i3.55
Hassan, M., Awan, F. M., Naz, A., Deandrés-Galiana, E. J., Alvarez, O., Cernea, A., Fernández-Brillet, L., Fernández-Martínez, J. L., & Kloczkowski, A. (2022). Innovations in genomics and big data analytics for personalised medicine and health care: A review. International Journal of Molecular Sciences, 23(9). https://doi.org/10.3390/ijms23094645
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018). Artificial intelligence in radiology. Nature Reviews Cancer, 18(8). https://doi.org/10.1038/s41568-018-0016-5
Iqbal, S. M. A., Mahgoub, I., Du, E., Leavitt, M. A., & Asghar, W. (2021). Advances in healthcare wearable devices. npj Flexible Electronics, 5(1). https://doi.org/10.1038/s41528-021-00107-x
Jackson, B. R., Ye, Y., Crawford, J. M., Becich, M. J., Roy, S., Botkin, J. R., de Baca, M. E., & Pantanowitz, L. (2021). The ethics of artificial intelligence in pathology and laboratory medicine: Principles and practice. Academic Pathology, 8. https://doi.org/10.1177/2374289521990784
Jin, D., Harrison, A. P., Zhang, L., Yan, K., Wang, Y., Cai, J., Miao, S., & Lu, L. (2020). Artificial intelligence in radiology. In Artificial Intelligence in Medicine: Technical Basis and Clinical Applications. https://doi.org/10.1016/B978-0-12-821259-2.00014-4
Kim, E., & Han, S. (2023). Investigating the digital health acceptance of Korean baby boomers: Comparative study of telemedicine and wearable healthcare devices. Health Policy and Technology, 12(1). https://doi.org/10.1016/j.hlpt.2023.100727
Kumar, P., Chauhan, S., & Awasthi, L. K. (2023). Artificial intelligence in healthcare: Review, ethics, trust challenges & future research directions. Engineering Applications of Artificial Intelligence, 120. https://doi.org/10.1016/j.engappai.2023.105894
Mondal, R. S., Bhuiyan, M. N. A., Akter, L. (2025). "AI-driven Innovations in Cancer Research and Personalised Healthcare", Integrative Biomedical Research (Journal of Angiotherapy), 9(1),1-10,10321
https://doi.org/10.25163/angiotherapy.9110321
Mondal, R. S., Bhuiyan, M. N. A., Akter, L. (2024). "Machine Learning for Chronic Disease Predictive Analysis for Early Intervention and Personalised Care", Applied IT & Engineering, 2(1),1-11,10301 https://doi.org/10.25163/engineering.2110301
Mondal, R. S., Akter, L., Bhuiyan, M. N. A. (2025). "Integrating AI and ML Techniques in Modern Microbiology", Applied IT & Engineering, 3(1),1-10,10323 https://doi.org/10.25163/engineering.3110323
Mondal, R. S., & Bhuiyan, M. N. A. (2024). Predictive Analytics for Chronic Disease Management: A Machine Learning Approach to Early Intervention and Personalised Treatment. Journal of Computational Analysis and Applications, 33(8).
Mondal, R. S., Bhuiyan, M. N. A., Kamruzzaman, M., Saha, S., & Siddiki, M. S. (2025). A Comparative Analysis of Outline of Tools for Data Mining and Big Data Mining. Journal of Business and Management Studies, 7(4), 232-242.
Mondal, R. S., Kamruzzaman, M., Saha, S., & Bhuiyan, M. N. A. (2025). Quantum Machine Learning Approaches for High-Dimensional Cancer Genomics Data Analysis. Computer Integrated Manufacturing Systems, 31(1), 13-32.
Niazi, M. K. K., Parwani, A. V., & Gurcan, M. N. (2019). Digital pathology and artificial intelligence. The Lancet Oncology, 20(5). https://doi.org/10.1016/S1470-2045(19)30154-8
Rabi Sankar Mondal, Lamia Akter, Md Nazmul Alam Bhuiyan. (2024). "Artificial Intelligence in Drug Development and Delivery: Opportunities, Challenges, and Future Directions", Journal of Angiotherapy, 8(1),1-10,10326
https://doi.org/10.25163/angiotherapy.8810326
Saha, S., Siddiki, M. S., Mondal, R. S., Bhuiyan, M. N. A., & Kamruzzaman, M. (2025). Risk Assessment of Cyber Security in the Banking Sector. Journal of Business and Management Studies, 7(4), 208-218.
Saha, S., Islam, M. K., Rahaman, M. A., & Mondal, R. S. (2024). Machine Learning Driven Analytics for National Security Operations: A Wavelet–Stochastic Signal Detection Framework. Journal of Computational Analysis and Applications, 33(8).
Siddique, M. A. B., Debnath, A., Nath, N. D., Biswash, M. A. R., Tufael (2018). "Advancing Medical Science through Nanobiotechnology: Prospects, Applications, and Future Directions", Journal of Primeasia, 1.1(1),1-7,10163
Serrano, D. R., Luciano, F. C., Anaya, B. J., Ongoren, B., Kara, A., Molina, G., Ramirez, B. I., Sánchez-Guirales, S. A., Simon, J. A., Tomietto, G., Rapti, C., Ruiz, H. K., Rawat, S., Kumar, D., & Lalatsa, A. (2024). Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionising Personalised Medicine. Pharmaceutics, 16(10), 1328. https://doi.org/10.3390/pharmaceutics16101328
Tufael, Atiqur Rahman Sunny et al. (2023). Artificial Intelligence in Addressing Cost, Efficiency, and Access Challenges in Healthcare, 4(1), 1-5, 9798
Tufael and Atikur Rahmen Sunnay (2022). Transforming Healthcare with Artificial Intelligence: Innovations, Applications, and Future Challenges, Journal of Primeasia, 3(1), 1-6, 9802