Abstract
Intelligent chatbot systems are popular applications in the fields of robotic and natural language processing. Nowadays, the strain on medical advisors encourages the use of healthcare chatbots to provide meditations and suggestions. In this paper, we have presented a dataset and a healthcare chatbot developed on the RASA framework that uses the NLP methods for disease detection and provides medical advice. The designed dataset has been verified and refined with the help of medical experts. The proficiency of the designed healthcare chatbot has been tested on the collected data using RASA test methods and validation. The model scored an F1-score of 77.3% and accuracy of 78.7%. Moreover, human evaluation achieves an accuracy of 56.50%. The dataset is publicly available at https://github.com/Medic-Bot-India/rasaModel.
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Acknowledgement
We would like to thank the Department of Computer Science and Engineering and the Center for Natural Language Processing (CNLP) at the National Institute of Technology Silchar for providing the requisite support and infrastructure to execute this work. The work presented here falls under the Student Innovation Grant Program of ARTPARK, a joint initiative of IISc Bangalore and AIfoundry, seed-funded by the Department of Science and Technology (DST) and the Government of Karnataka.
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Mishra, P. et al. (2022). Personalized Healthcare Chatbot: Dataset and Prototype System. In: Mukhopadhyay, S., Sarkar, S., Dutta, P., Mandal, J.K., Roy, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2022. Communications in Computer and Information Science, vol 1579. Springer, Cham. https://doi.org/10.1007/978-3-031-10766-5_30
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