Designing a chatbot to analyze patient sentiment: The case of the Sangarébougou Community Health Center

Résumé

This paper examines the integration of deep learning and natural language processing to develop medical chatbots that provide diagnoses and recommendations based on user-provided symptoms. The rural commune of Sangarébougou in Mali serves as a case study for the development and deployment of the chatbot. The work covers data collection and preprocessing, textual analysis and tokenisation, and the use of NLP and deep learning algorithms to train the chatbot model. The results show that modern NLP and deep learning techniques can support automated medical assistance and improve healthcare accessibility in rural areas.