Authors : Srujan K. B.; Ashvitha A.; Dr. Divya A. K.; Dr. Bala Pradeep K. N.

Volume/Issue : Volume 11 - 2026, Issue 5 - May

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Google Scholar : https://tinyurl.com/4aectt6a

Scribd : https://tinyurl.com/3hkz3xym

DOI : https://doi.org/10.38124/ijisrt/26May484

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : Effective patient-provider communication is severely hampered by the growing linguistic diversity in international healthcare systems, which frequently results in misunderstandings, lower-quality care, and restricted accessibility. The integration of domain-specific language models, semantic interoperability, and AI-driven conversational frameworks are the key topics of this paper's thorough examination of NLP-based multilingual medical communication systems. To guarantee precise cross-lingual translation and the preservation of clinical semantics, the suggested method makes use of multilingual Natural Language Processing techniques in conjunction with medical ontology alignment (e.g., UMLS, SNOMED CT).

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