Virtual Patient – An AI-based System for Training in Cardiovascular Diseases Diagnostic and Treatment
Virtual patients are able to represent patients in realistic clinical scenarios and engage learners in doctor-patient conversations about the patient’s health, interpret laboratory results and medical images, and form a diagnosis. Currently, due to the conditions created by the COVID-19 pandemic, the interaction of medical students with patients is limited, therefore virtual doctor-patient interaction environments become a safe and practical solution for training medical skills, including blended learning. With the current advances in artificial intelligence, virtual patients can be equipped with advanced functions, such as the integration of different types of conversational agents or support for the automatic prediction of the patient’s evolution.
In this context, the main objective of the project is to develop a virtual environment to simulate the interactions between the learner (medical student or doctor/resident) and a virtual clinical patient for the diagnosis and treatment of acute and chronic heart diseases. The virtual environment, supported by a software platform and artificial intelligence technologies, simulates real-life clinical scenarios in which the student emulates the role of the doctor who performs an examination of the virtual patient and obtains a history, performs anamnesis, physical examination, paraclinical investigations, establishes a diagnosis and recommends a therapeutic plan.