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

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.

Authors

Publication Details

Journal
Engineering Technology & Applied Science Research
Published
2025-04-03
DOI
https://doi.org/10.48084/etasr.9484
Citations
2
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
1.61
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article

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

Muhammad Ali, Rozana Othman, Wassim Zahrouni, Albia Maqbool et al.
2 citations
Engineering Technology & Applied Science Research
Biomedical Text Mining and Ontologies
1.61
article

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

Muhammad Ali, Rozana Othman, Wassim Zahrouni, Albia Maqbool, Dima Mahmoud Aref Abbadi, Khaled Mejdi, Nargis Parveen, Esraa M. Al-Lobani, Hina Skhawat, Shama Mashhour M. Alqahtani
article en
2 citations

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.

Engineering Technology & Applied Science ResearchVol. 15(2)
Openalex Percentile: Top 18%
Biomedical Text Mining and Ontologies
1.61
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A Multi-Language NLP Model for Inclusive Digital Healthcare Marketing and Patient Communication — Muhammad Ali, Rozana Othman, et al. · Engineering Technology & Applied Science Research (2025) | TGRS Research Map | TGRS