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@article{164820,
        author = {Sakshi Rai and Ujawal Rai and Sharda Dabhekar},
        title = {Symptom checker chatbot},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {2215-2217},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164820},
        abstract = {Our study introduces a chatbot for preliminary disease diagnosis, employing Flask, NLP, and machine learning techniques. Through Spacy's pre-trained model, the chatbot extracts symptom keywords, which are vectorized using TF-IDF and fed into a Random Forest classifier. The chatbot provides users with accurate disease predictions, enriched with dynamically integrated disease descriptions and precautions. This fusion of NLP and machine learning demonstrates a scalable approach to healthcare technology.},
        keywords = {Extraction: Spacy was used to tokenize the text and extract keywords, filtering out stop words and non-alphabetic tokens.},
        month = {},
        }