BUILDING A CHATBOT TO SUPPORT CONSULTATION ON COMMON DERMATOLOGICAL DISEASES

Abstract

The thesis aims to build a Chatbot system that makes dermatology diagnoses faster, easier and more transparent for both patients and doctors – using machine learning to provide increasingly accurate answers to patients. The user's questions are based on behaviors it "learns" by interacting with humans. Chatbots in the field of dermatology reduce the workload of healthcare professionals by reducing hospital visits, reducing unnecessary treatments and procedures, and reducing the number of visits. hospital as their adherence to treatment and knowledge of their symptoms improved. For patients, this brings a lot of benefits: • Reduce travel time to the doctor's office • Reduce funding for unnecessary treatments and tests • Easy access to a doctor through the app This thesis will focus on researching techniques to build Chatbot, including: natural language processing techniques, intent classification, information extraction, conversation management using RASA platform to develop and build Chatbot application interface in the dermatology industry, combining intelligent NLP systems with machine learning technology to provide users with an accurate and responsive experience.