AI Based Symptom Checker App Using NLP and Machine Learning

Abstract

In the digital age, the need for quick and reliable access to healthcare information is increasingly essential. This project introduces an AI-powered Symptom Checker Application that leverages Natural Language Processing (NLP) and Machine Learning (ML) to interpret user-described symptoms and forecast possible diseases.Through NLP processes such as tokenization, lemmatization, and Named Entity Recognition (NER), the application converts free-form text into structured data. This processed information is then analyzed by ML models like Naïve Bayes, Random Forest, and Support Vector Machine (SVM) to estimate probable medical conditions.Acting as a virtual medical assistant, the system offers users an initial understanding of their health concerns, helping them make informed decisions before consulting a doctor. By integrating AI technologies, the project enhances healthcare accessibility, supports preventive diagnosis, and minimizes misinformation from unreliable sources.