Demonstrates a healthcare support system's effectiveness in scheduling and specialist recommendation, indicating improved patient care.
This work presents a healthcare support system that uses machine learning to recommend the appropriate medical specialist based on user symptoms. The system applies TF-IDF feature extraction and compares Naïve Bayes, SVM, and Random Forest models, where Naïve Bayes achieved the best performance. It also includes severity assessment and smart appointment scheduling.
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Teja Ravi Hulse (2026) studied this question.
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