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AI-Driven Privacy-Preserving Healthcare System for Disease Prediction and Personalized Care
Authors
1 2 3 4 5 Department of Artificial Intelligence and Machine Learning, SASI Institute of Engineering and Technology, Tadepalligudem, Andhra Pradesh, India.
Article Information
- Organised By
- Madanapalle Institute of Technology & Science (MITS)
- Conference Date
- 9 & 10 March 2026
- Pages
- 78-84
- Article Type
- Research Article
- Check for updates
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References
1. J. Lee, W. Yoon, S. Kim, et al., "BioBERT: a pre-training biomedical language representation model for biomedical text mining," Bioinformatics, vol. 36, no. 4, pp. 1234-1240, 2019.
2. Y. Peng, S. Yan, and Z. Lu, "Transfer learning on biomedical natural language processing: Benchmarking BERT and ELMo on 10 biomedical natural language processing datasets," Bioinformatics, vol. 35, no. 8, pp. 1322--1329, 2019.
3. S. K. Shyni Sharaf and V. S. Anoop "An Analysis on Large Language Models in Healthcare: A Case Study of BioBERT" arXiv. 2023
4. "AI Enhanced Symptom Checker Using BioBERT for Disease Prediction" International Journal of Scientific Research & Engineering Trends, vol. 11, no. 2, pp. 413-420, 2025.
5. S. Aydin, A. R. H. Ali, S. Faiz, and T. A. Khan, "An Integrated Artificial Intelligence Framework for Personalized Nutrition via Machine Learning and Natural Language Processing for Dietary Recommendations," Applied Sciences, vol. 15, no. 17, pp. 9283-9295, 2025.
6. M. Hamid, et. al., "Fine-tuned CatBoost machine learning approach for early cardiovascular disease classification" PMC, vol. 10, no. 3, p. 215--221, 2025.
7. S. M. Alqrinawi, M. A. Burhanuddin, and L. Salahuddin, "CatBoost Approach for Predicting Personalized Treatment of Type 2 Diabetes," JISEM Journal, vol. 13, no. 2, pp. 146-154, 2025.
8. K. Foster, N. Costadopoulos, A. Mahboubi, S. U. Rehman and M. Z. Islam, "Toward Privacy-Preserving Data Sharing - An Australian Healthcare Perspective," in Proceedings of the Florence, Italy, 2025, in Computers in Human Behavior, vol. 13, pp. 39405-39427.
9. B. H. M. van der Velden, H. J. Kuijf, K. G. A. Gilhuijs, and M. A. Viergever, "Explainable artificial intelligence (XAI) in deep learning based medical image analysis: A survey," Medical Image Analysis, vol. 79, pp. 101-115, 2022.
10. M. Hanani, G. Kulawardana, D. De Silva, et al., "Explainable AI using integrated gradients for detecting adversarial attacks on text classifiers," in Applied System Innovation, vol. 8, no. 1, pp. 17--28, 2025.
11. "Explainable Artificial Intelligence for Medical Applications: A Review," International Journal of Artificial Intelligence Applications, vol. 25, no. 3, pp. 45-60, 2025.
12. "Towards disease prediction system: BioBERT based medical profile representation," International Journal of Artificial Intelligence vol. 15, no. 1, pp. 34-40, 2024.
13. M. Zonayed, R. Tasnim, S. Sultana Jhara, et al., "Machine Learning and IoT in Healthcare: advancements & challenges," ScienceDirect, vol. 11, pp. 34-45, 2025.
14. S. Sharaf, V. S. Anoop, et al. "BioGPT: Generative pre-trained transformer for biomedical text generation and mining" arXiv, 2022.
15. R. Shokri and V. Shmatikov, "Privacy Preserving Deep Learning," in Proc. 22nd ACM CCS, 2015, pp. 1310-1321.
2. Y. Peng, S. Yan, and Z. Lu, "Transfer learning on biomedical natural language processing: Benchmarking BERT and ELMo on 10 biomedical natural language processing datasets," Bioinformatics, vol. 35, no. 8, pp. 1322--1329, 2019.
3. S. K. Shyni Sharaf and V. S. Anoop "An Analysis on Large Language Models in Healthcare: A Case Study of BioBERT" arXiv. 2023
4. "AI Enhanced Symptom Checker Using BioBERT for Disease Prediction" International Journal of Scientific Research & Engineering Trends, vol. 11, no. 2, pp. 413-420, 2025.
5. S. Aydin, A. R. H. Ali, S. Faiz, and T. A. Khan, "An Integrated Artificial Intelligence Framework for Personalized Nutrition via Machine Learning and Natural Language Processing for Dietary Recommendations," Applied Sciences, vol. 15, no. 17, pp. 9283-9295, 2025.
6. M. Hamid, et. al., "Fine-tuned CatBoost machine learning approach for early cardiovascular disease classification" PMC, vol. 10, no. 3, p. 215--221, 2025.
7. S. M. Alqrinawi, M. A. Burhanuddin, and L. Salahuddin, "CatBoost Approach for Predicting Personalized Treatment of Type 2 Diabetes," JISEM Journal, vol. 13, no. 2, pp. 146-154, 2025.
8. K. Foster, N. Costadopoulos, A. Mahboubi, S. U. Rehman and M. Z. Islam, "Toward Privacy-Preserving Data Sharing - An Australian Healthcare Perspective," in Proceedings of the Florence, Italy, 2025, in Computers in Human Behavior, vol. 13, pp. 39405-39427.
9. B. H. M. van der Velden, H. J. Kuijf, K. G. A. Gilhuijs, and M. A. Viergever, "Explainable artificial intelligence (XAI) in deep learning based medical image analysis: A survey," Medical Image Analysis, vol. 79, pp. 101-115, 2022.
10. M. Hanani, G. Kulawardana, D. De Silva, et al., "Explainable AI using integrated gradients for detecting adversarial attacks on text classifiers," in Applied System Innovation, vol. 8, no. 1, pp. 17--28, 2025.
11. "Explainable Artificial Intelligence for Medical Applications: A Review," International Journal of Artificial Intelligence Applications, vol. 25, no. 3, pp. 45-60, 2025.
12. "Towards disease prediction system: BioBERT based medical profile representation," International Journal of Artificial Intelligence vol. 15, no. 1, pp. 34-40, 2024.
13. M. Zonayed, R. Tasnim, S. Sultana Jhara, et al., "Machine Learning and IoT in Healthcare: advancements & challenges," ScienceDirect, vol. 11, pp. 34-45, 2025.
14. S. Sharaf, V. S. Anoop, et al. "BioGPT: Generative pre-trained transformer for biomedical text generation and mining" arXiv, 2022.
15. R. Shokri and V. Shmatikov, "Privacy Preserving Deep Learning," in Proc. 22nd ACM CCS, 2015, pp. 1310-1321.
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