An Ai-based Medical Chatbot For Infectious Disease Prediction Using Multi-layer Perceptron

Abstract

The Rapid Growth Of Digital Health Technologies Has Created New Opportunities For Accessible And Early Disease Detection. This Project Proposes An Intelligent Chatbot-based System Capable Of Providing Preliminary Disease Diagnosis Using Machine Learning. The Chatbot Interacts With Users Through A Conversational Interface, Collects Symptom Inputs, And Analyzes Them Using Trained ML Models Such As Naïve Bayes, Decision Trees, Or Support Vector Machines. The System Is Designed To Classify Possible Diseases Based On Symptom Patterns And Return Probable Diagnoses Along With Recommended Next Steps, Such As Consulting A Specialist Or Seeking Emergency Care. The Chatbot Also Offers Continuous Guidance, Clarifying Symptoms And Providing Health-awareness Information In Real Time. The Integration Of NLP Enables The System To Understand Natural User Queries, Making It User-friendly And Accessible Even To Individuals With Limited Medical Knowledge. Experimental Results Demonstrate That ML-based Prediction Significantly Improves Diagnostic Accuracy Compared To Rule-based Systems. This Solution Can Support Rural Healthcare, Reduce Clinical Workload, And Provide Immediate Preliminary Medical Assistance, Serving As A Low-cost, Scalable Tool For Early Disease Detection And Decision Support.

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