AI Powered Medical Chatbot in Vernacular Languages

This research paper aims to investigate the feasibility and efficacy of deploying medical chatbots in vernacular languages, with the objective of bridging the communication gap between healthcare seekers and providers in linguistically diverse regions. To achieve this, the study adopts a comprehensive mixed-methods approach that incorporates qualitative interviews and quantitative user feedback analysis. The primary focus is to develop a robust vernacular language medical chatbot framework that can effectively address the linguistic and cultural requirements of the target populations. Additionally, the research evaluates the effectiveness of the chatbot in delivering accurate and relevant healthcare information in vernacular languages by comparing the user feedback analysis with responses from human experts. Furthermore, the study explores the broader impact of implementing vernacular language medical chatbots on various aspects, including healthcare accessibility, patient empowerment, and overall healthcare outcomes. The participation of individuals from diverse linguistic backgrounds adds invaluable insights into their experiences, perceptions, and suggestions, thus enabling a comprehensive understanding of the usability, accuracy, and effectiveness of the vernacular language medical chatbot. The outcomes of this research will contribute significantly to the development and optimization of tailored chatbot systems that effectively address linguistic barriers, benefiting policymakers, healthcare providers, and technology developers alike. By promoting equitable healthcare access, enhancing patient engagement, and improving healthcare outcomes in linguistically diverse communities, this research endeavor strives to advance the field of healthcare by optimizing the design and deployment of vernacular language medical chatbots, ultimately leading to improved healthcare accessibility and quality of care.