Privacy-Preserving Integration of GPT-4 and Natural Language Processing via Secure Multi-Party Computation for Healthcare Data
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.
Authors
- Salah A. Aliesawi (ORCID: https://orcid.org/0000-0002-3157-781X)
- Korhan Cengiz (ORCID: https://orcid.org/0000-0001-6594-8861)
- Abdullah Lakhan (ORCID: https://orcid.org/0000-0002-1833-1364)
- Mohd Khanapi Abd Ghani (ORCID: https://orcid.org/0000-0002-3074-8795)
- Narjes Benameur
- Mazin Abed Mohammed (ORCID: https://orcid.org/0000-0001-9030-8102)
- Zainab Khalid Mohammed
Institutions
- VSB - Technical University of Ostrava (CZ)
- University of Zagreb (HR)
- University of Anbar (IQ)
- Technical University of Malaysia Malacca (MY)
- Dawood University of Engineering and Technology (PK)
- Tunis El Manar University (TN)
Publication Details
- Journal
- International Journal of Mathematics Statistics and Computer Science
- Published
- 2025-07-12
- DOI
- https://doi.org/10.59543/ijmscs.v3i.15181
- Citations
- 2
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 4.96