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- Vol. 6 Issue 2
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AI-Driven Treatment Response Prediction for Chronic Disease Management Using Generative Artificial Intelligence and Large Language Models
Authors
1 Associate Professor, Nawab Shah Alam Khan College of Engineering and Technology, Hyderabad, Telangana., India. 2 Associate Professor, Deccan College of Engineering and Technology, Hyderabad, Telangana., India.
Article Information
- Published In
- Volume 6, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 58-65
- Article Type
- Original Article
References
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A critical review,” IEEE Access, vol. 12, pp. 80698–80730, 2024.
2. C. Wu, S. Wang, and Y. Su, “A precision health service for chronic diseases using wearable devices, machine learning, and deep learning,”
IEEE Journal of Translational Engineering in Health and Medicine, vol. 10, pp. 1–14, 2022.
3. S. Rani and P. Singh, “Machine learning powered smart healthcare systems using big data analytics,” IEEE Access, vol. 13, pp. 10023–
10045, 2025.
4. A. Guerra-Manzanares, J. Lechuga Lopez, M. Maniatakos, and F. Shamout, “Privacy-preserving machine learning for healthcare: Open
challenges and future perspectives,” IEEE Access, vol. 11, pp. 45782–45805, 2023.
5. F. Mohsen, H. Ali, N. El Hajj, and Z. Shah, “Artificial intelligence-based methods for fusion of electronic health records and imaging
data,” IEEE Access, vol. 10, pp. 124856–124874, 2022.
6. L. Mondrejevski, I. Miliou, A. Montanino, D. Pitts, J. Hollmén, and P. Papapetrou, “FLICU: A federated learning workflow for ICU
mortality prediction,” IEEE Access, vol. 10, pp. 62310–62322, 2022.
7. S. Rani, A. Verma, and M. Singh, “Artificial intelligence and big data analytics for personalized healthcare systems,” IEEE Access, vol.
11, pp. 118903–118918, 2023.
8. H. Younis, T. Eisa, and M. Nasser, “Artificial intelligence tools in healthcare: Applications, challenges, and future directions,” IEEE
Access, vol. 12, pp. 45120–45136, 2024.
9. M. Bouqentar, A. A. Ahmed, and M. Khalid, “Early heart disease prediction using feature engineering and machine learning techniques,”
IEEE Access, vol. 12, pp. 75531–75545, 2024.
10. S. N. Tisha and S. A. Ani, “Predictive insights: Empowering early detection of lung cancer using machine learning,” in Proc. IEEE Region
10 Symposium (TENSYMP), 2024.
11. D. Singh, A. Khandelwal, P. Bhandari, S. Barve, and D. Chikmurge, “Predicting lung cancer using XGBoost and ensemble learning
models,” in Proc. IEEE ICCCNT, 2023.
12. A. Vishwakarma, A. Saini, K. Guleria, and S. Sharma, “Early prognosis of lung cancer using machine intelligence,” in Proc. IEEE ICAIA,
2023.
13. B. S. Ramesh, P. Rajesh, and A. Babu, “Lung cancer detection using machine learning,” in Proc. IEEE International Conference on
Applied Artificial Intelligence and Computing, 2022.
14. M. Mamun, A. Farjana, M. Al Mamun, and M. Ahammed, “Lung cancer prediction model using ensemble learning techniques,” in Proc.
IEEE World AI IoT Congress, 2022.
15. M. Inoue et al., “Disease prediction using machine learning and mobile healthcare data,” IEEE Journal of Biomedical and Health
Informatics, vol. 29, no. 1, pp. 55–67, 2025.
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