A Multi-Language NLP Model for Inclusive Digital Healthcare Marketing and Patient Communication
Year: 2025
Type: article
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.
DOI: 10.48084/etasr.9484
Authors: 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
Institution: Northern Border University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $431
OpenAlex ID: W4409173718
