Privacy-Preserving Integration of GPT-4 and Natural Language Processing via Secure Multi-Party Computation for Healthcare Data

Authors

  • Zainab Khalid Mohammed Engineering of Communication and Information Technology, Ministry of Water Resources, Baghdad, Iraq Author
  • Mazin Abed Mohammed Department of Artificial Intelligence, College of Computer Science and Information Technology, University of Anbar, Anbar, 31001, Iraq and Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic. https://orcid.org/0000-0001-9030-8102 Author
  • Mohd Khanapi Abd Ghani Department of Software Engineering, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia. https://orcid.org/0000-0002-3074-8795 Author
  • Salah A. Aliesawi Department of Artificial Intelligence, College of Computer Science and Information Technology, University of Anbar, Anbar, 31001, Iraq. https://orcid.org/0000-0002-3157-781X Author
  • Narjes Benameur Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar, Tunis, Tunisia. https://orcid.org/0000-0002-3911-1416 Author
  • Korhan Cengiz Faculty of Organization and Informatics, University of Zagreb, Croatia. https://orcid.org/0000-0001-6594-8861 Author
  • Abdullah Lakhan Department of Cybersecurity and Computer Science, Dawood University of Engineering and Technology, Karachi City 74800, Sindh, Pakistan. https://orcid.org/0000-0002-1833-1364 Author

DOI:

https://doi.org/10.59543/ijmscs.v3i.15181

Keywords:

Artificial Intelligence, Healthcare, GPT-4, Natural Language Processing, Secure Multi-Party Computation.

Abstract

Integrating Generative Pre-Trained Transformer (GPT-4) in healthcare heralds a transformative era, automating routine tasks and empowering physicians to focus on complex patient care. GPT-4's role in patient education simplifies medical terminology, fosters a knowledgeable patient base, and promotes adherence to care plans. This study presents a secure framework for integrating GPT-4, Natural Language Processing (NLP), and patient data in healthcare using Secure Multi-Party Computation (MPC). The framework ensures secure data exchange among stakeholders in healthcare data analysis. Emphasizing security, privacy, and regulatory compliance, the study underscores collaboration with privacy, security, and healthcare experts. The amalgamation of GPT-4 and NLP advances research and care and upholds data protection standards. The revolutionary use of MPC marks a paradigm shift, promising enhanced patient outcomes and securing the future of healthcare.

Downloads

Published

2025-07-12

How to Cite

Zainab Khalid Mohammed, Mazin Abed Mohammed, Mohd Khanapi Abd Ghani, Salah A. Aliesawi, Narjes Benameur, Korhan Cengiz, & Abdullah Lakhan. (2025). Privacy-Preserving Integration of GPT-4 and Natural Language Processing via Secure Multi-Party Computation for Healthcare Data. International Journal of Mathematics, Statistics, and Computer Science, 3, 390-407. https://doi.org/10.59543/ijmscs.v3i.15181

Issue

Vol. 3 (2025)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

IJMSCS is published Open Access under a Creative Commons CC-BY 4.0 license. Authors retain full copyright, with the first publication right granted to the journal.