Medical communication: Designing an enhanced health care chatbot for instructive conversations

The increasing demand for healthcare advice necessitates innovative solutions to bridge the doctor-to-patient gap. Maintaining a healthy body is the first goal of today’s generation; seeing the rapid advancement in technology, people have using technology to ease the access of healthcare tips. Recent pandemic, COVID-19 has shown us how much important having a constant advice regarding our health has become. This paper proposes a novel desig-n for a real-time medical chatbot that utilizes a combination of Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine Learning (ML) to deliver a personalized and professional user experience. Our key differentiator lies in the real- time doctor interaction mechanism. Beyond relying solely on pre-trained datasets, the chatbot continuously learns and refines its responses by interacting with real doctors. This nurtures adaptation to real-world doctor-patient communication patterns, enabling the chatbot to handle complex queries and provide a more professional touch. The pre-processing stage utilizes a robust combination of NLP techniques like n-gram, TF-IDF, and intent classification to ensure accurate understanding of user intent. Additionally, a dedicated knowledge base stores and retrieves medical information. This medical chatbot design aims to transform in-person care by offering primary healthcare education and personalized guidance, ultimately empowering individuals to manage their health more effectively.