An Implementation of Machine Learning Based Healthcare Chabot for Disease Prediction (MIBOT)

In an era where quality healthcare is pivotal for a successful life journey, challenges arise when seeking medical attention amid the ongoing pandemic. The traditional approach of consulting doctors in person or visiting hospitals is hindered, emphasizing the necessity for innovative solutions. Harnessing the capabilities of Natural Language Processing (NLP) and machine learning, this study introduces an advanced chatbot application. Built upon supervised machine learning, the proposed chatbot system not only offers disease diagnosis and comprehensive treatment insights but also does so preemptively, prior to consulting a physician. This system boasts a user-friendly GUI-based text assistant, facilitating seamless interaction with the chatbot. Unlike existing models, this approach intelligently presents user symptoms and corresponding risk factors, tailored to the user's ailment, while also offering optimal recommendations. Moreover, the chatbot clarifies the appropriate instances for in-person medical consultations. By addressing the underutilization highlighted in previous research, this study signifies the chatbot's potential advantages. By embracing this cost-free application, individuals can circumvent cumbersome hospital visits. The comparison with the reference model demonstrates the enhanced efficacy of the proposed approach in addressing healthcare challenges, ensuring convenient and accessible medical guidance.