Paper Title
Bridging the Gap: On-Device Machine Learning for Multilingual Telemedicine in Remote Communities
Article Identifiers
Registration ID: IJNRD_224638
Published ID: IJNRD2311396
DOI: https://doi.org/10.5281/zenodo.14869134
Authors
Sivaramarajalu Ramadurai Venkataraajalu , Priyadarshini SRP
Keywords
Telemedicine, Remote Communities, Multilingual, On-Device, Machine Learning, Edge Computing, Healthcare
Abstract
This paper proposes an innovative healthcare system for remote communities, integrating on-device machine learning, telemedicine, and multilingual natural language processing. The system aims to overcome geographical, resource, and language barriers in healthcare access by providing initial diagnosis and triage on patients' mobile devices, facilitating real-time translation for patient-system interaction, and enabling secure telemedicine consultations. Key features include adaptable on-device diagnostic models, multilingual communication capabilities, emergency response coordination, and integration with electronic health records. The paper discusses the system's technical architecture, the critical role of medical professionals in its implementation and continuous improvement, and associated ethical considerations. By combining advanced technology with human expertise, this approach has the potential to significantly enhance healthcare accessibility and outcomes in underserved areas, contributing to the global goal of universal health coverage.
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How To Cite (APA)
Sivaramarajalu Ramadurai Venkataraajalu & Priyadarshini SRP (November-2023). Bridging the Gap: On-Device Machine Learning for Multilingual Telemedicine in Remote Communities. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(11), d877-d883. https://doi.org/10.5281/zenodo.14869134
Issue
Volume 8 Issue 11, November-2023
Pages : d877-d883
Other Publication Details
Paper Reg. ID: IJNRD_224638
Published Paper Id: IJNRD2311396
Downloads: 000121980
Research Area: Medical Science
Country: Hackensack, New Jersey, United States
Published Paper PDF: https://ijnrd.org/papers/IJNRD2311396.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2311396
Crossref DOI: https://doi.org/10.5281/zenodo.14869134
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