Authors - S. Rahul, Anusha Preetham, Aniketh Patil, Abhishek Nimbal, Sahana Meti Abstract - This paper introduces Dr. BOT, a comprehensive web-based healthcare application designed to overcome language barriers in medical communication across diverse linguistic environments. While initially trained to predict several diseases including diabetes, heart disease, kidney disease, liver disease, and breast cancer, the system's architecture enables expansion to detect and interpret a wide range of medical conditions. Dr. BOT employs robust machine learning algorithms (Random Forest, Support Vector Machine, and Logistic Regression) trained on validated datasets, with special emphasis on multilingual functionality through a hybrid approach combining NLP with neural machine translation models specifically finetuned for medical terminology. The platform operates effectively in low-connectivity environments through innovative offline capabilities, offering preventive healthcare guidance and localized medical resource information in users' native languages, thereby supporting both individuals and healthcare providers in improving health outcomes globally.
