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A Multi-Language NLP Model for Inclusive Digital Healthcare Marketing and Patient Communication

Authors

  • Nargis Parveen Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia
  • Albia Maqbool Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia
  • Hina Skhawat Department of Basic Sciences, Applied College, Northern Border University, Saudi Arabia
  • Rima Osama Mohammad Othman Department of Administrative Sciences, Applied College, Northern Border University, Saudi Arabia
  • Dima Mahmoud Aref Abbadi Department of Administrative Sciences, Faculty of Applied College, Northern Border University, Saudi Arabia
  • Esraa M. Al-Lobani Department of Mathematics Sciences, Faculty of Applied College, Northern Border University, Saudi Arabia
  • Shama Mashhour M. Alqahtani Department of Basic Sciences, Applied College, Northern Border University, Saudi Arabia
  • Muhammad Skhawat Ali Department of Basic Sciences, Applied College, Northern Border University, Saudi Arabia
  • Khaled Mejdi Department of Administrative sciences, Applied College, Northern Border University, Rafha, Saudi Arabia
  • Wassim Zahrouni Department of Finance and Insurance, College of Business Administration, Northern Border University, Saudi Arabia
Volume: 15 | Issue: 2 | Pages: 21045-21054 | April 2025 | https://doi.org/10.48084/etasr.9484

Received: 2 November 2024 | Revised: 5 December 2024, 16 December 2024, and 23 December 2024 | Accepted: 29 December 2024 | Online: 5 February 2025


Corresponding author: Albia Maqbool

Abstract

Digital healthcare systems integrate Natural Language Processing (NLP) to make advances in the ways patients engage and communicate. However, multilingual access to a wide variety of languages has been an ongoing problem. This study introduces a multilingual NLP model for digital healthcare marketing and patient communication, designed to help patients obtain health information across languages. This work addresses essential multilingual issues in the healthcare context, such as providing a language-adaptive function using state-of-the-art semantic processing. The model introduces linguistic diversity for personalized healthcare marketing to help develop more personal relationships with patients. The model was evaluated across languages to determine whether it provides practical benefits in enabling clear and culturally attuned communication. This model has the potential to help create a linguistically inclusive healthcare environment, helping patients understand their health conditions and treatment options, and increasing overall patient satisfaction.

Keywords:

natural language processing, multi-language model, digital healthcare marketing, patient communication, inclusivity, language adaptation, healthcare management

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How to Cite

[1]
Parveen, N., Maqbool, A., Skhawat, H., Othman, R.O.M., Abbadi, D.M.A., M. Al-Lobani, E., Alqahtani, S.M.M., Ali, M.S., Mejdi, K. and Zahrouni, W. 2025. A Multi-Language NLP Model for Inclusive Digital Healthcare Marketing and Patient Communication. Engineering, Technology & Applied Science Research. 15, 2 (Apr. 2025), 21045–21054. DOI:https://doi.org/10.48084/etasr.9484.

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Copyright (c) 2025 Nargis Parveen, Albia Maqbool, Hina Skhawat, Rima Osama Mohammad Othman, Dima Mahmoud Aref Abbadi, Esraa M. Al-Lobani, Shama Mashhour M. Alqahtani, Muhammad Skhawat Ali, Khaled Mejdi, Wassim Zahrouni

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