Symptom checker chatbot
Sakshi Rai, Ujawal Rai, Sharda Dabhekar
Extraction: Spacy was used to tokenize the text and extract keywords, filtering out stop words and non-alphabetic tokens.
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.
Article Details
Unique Paper ID: 164820

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 2215 - 2217
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