AI Healthcare Assistant using Machine Learning and NLP

This paper presents an AI-based Healthcare Assistant that integrates Natural Language Processing (NLP), Machine Learning (ML), Optical Character Recognition (OCR), and Deep Learning techniques for preliminary medical guidance. The system processes user inputs including text symptoms, speech input, scanned medical reports, and chest X-ray images. BioBERT is used for symptom extraction, a machine learning classifier predicts possible diseases, Tesseract OCR digitizes medical reports, and a Convolutional Neural Network (CNN) analyzes X-ray images for pneumonia detection. Experimental evaluation shows 96.2% accuracy in symptom extraction, 94.5% disease prediction accuracy, 97.1% X-ray classification accuracy, and 95.8% OCR reliability. The proposed system aims to enhance healthcare accessibility in rural and underserved regions.