• PV Sai Sivaram
• Mr. D. Nagaraju

Healthcare plays a crucial role in maintaining a good quality of life. However, scheduling appointments with doctors can be quite challenging, especially during emergencies. To address this issue, an innovative solution is being proposed - an application featuring a medical chatbot powered by Machine Learning. This chatbot will be able to diagnose illnesses and provide appropriate medical instructions and precautions in case of accidents. By utilizing this technology, the aim is to reduce the need for frequent doctor consultations and enhance the patient's medical knowledge. Through pattern matching, the chatbot can predict the patient's symptoms accurately. Additionally, the application integrates with Google Maps API to assist doctors in accessing and updating the patient's medication profile, eliminating the need for carrying physical prescriptions at all times. The development and implementation of a healthcare chatbot system powered by ML / NLP is detailed in this document. The system, created using Python in PyCharm IDE and Django framework, allows for user login, symptom input, accurate disease predictions, personalized solutions, and doctor recommendations. Machine learning algorithms utilizing Pandas, NumPy, Sklearn, and gensim libraries drive disease prediction and solution recommendation features. Evaluation results indicate high accuracy in disease prediction and relevance in solution provision. Ethical considerations, including data privacy and user trust, are carefully considered, representing a significant step forward in improving healthcare accessibility and setting the stage for future advancements in ML-driven healthcare services.

CHATBOT USING NLP

"CHATBOT USING NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.189-193, June-2024, Available :http://www.jetir.org/papers/JETIRGL06033.pdf

"CHATBOT USING NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp189-193, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06033.pdf