Medicine Recommendation System Using NLP(Natural Language Processing)
摘要
A Medicine Recommendation System intended to use user-provided symptoms to identify possible diseases and provide personalized suggestions for safety measures, diets, drugs, and exercise regimens. The system predicts symptoms using Natural Language Processing (NLP) and Fuzzy Matching, guaranteeing accurate identification even in the presence of noisy inputs. It makes predictions about likely diseases and obtains overarching information for each by comparing extracted symptoms with a disease-symptom dataset. The system, which was developed with the Flask framework, provides an intuitive online interface for smooth communication. This initiative aims to direct users toward informed medical treatment by showcasing potential in early disease identification. Future research will concentrate on improving accessibility more broadly and integrating healthcare data in real-time.