Virtual Patient

An AI-based System for Training in Cardiovascular Diseases Diagnostic and Treatment

Project Number PN-III-P2-2.1-PED-2021-2511

Details about the Project

Virtual Patient

An AI-based System for Training in Cardiovascular Diseases Diagnostic and Treatment

Project Number PN-III-P2-2.1-PED-2021-2511

Details about the Project

About the Project

Virtual Patient

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.

Starting from our already developed system, the challenges of this project are to advance virtual patient technology by developing a flexible and integrated cardiology training environment that incorporates advanced artificial intelligence techniques, especially case diagnosis and treatment planning simple and complex, a conversational agent capable of dialogue in natural language and voice, as well as the generation of synthetic data based on deep neural networks.

Artificial Intelligence

Short text about Artificial intelligence.

Patient Avatar

Short text about the avatar of the patient.

Interactions Simulation

Short text about the interactions simulation.

1098

Training Sessions

312

Case Scenarios

7

Cases

178

Users

Funding

Virtual Patient

This project is funded by the Ministry of Education and Research, CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2021-2511.

UEFISCDI
Implementation Team

Virtual Patient

Prof. Adina Magda Florea

Prof. Adina
Magda Florea

Project Director,
Professor, UNSTPB
Dr. Alexandru Scafa-Udriște

Dr. Alexandru
Scafa-Udriște

Doctor,
Professor, UMFCD
Maria Dorobantu

Dr. Maria
Dorobantu

Doctor,
Professor, UMFCD
Alex Awada

Alex Awada

Engineer,
Researcher, UNSTPB
Sebastian Onciul

Dr. Sebastian
Onciul

Doctor,
Researcher, UMFCD
Costin Minoiu

Dr. Costin Minoiu

Doctor,
Researcher, UMFCD
Cosmin Cojocaru

Dr. Cosmin
Cojocaru

Doctor,
Assistant Professor, UMFCD
Dissemination and Communication

2024

Journal Article: Imad Alex Awada, Adina Magda Florea, Alexandru Scafa-Udriște - A Virtual Case Presentation Platform: Protocol Study, Methods and Protocols Jurnal, Vol. 7, Iss. 2, 23, DOI: 10.3390/mps7020023, ISSN: 2409-9279, 2024.

Presentation: Alexandru Scafa-Udriște, Imad Alex Awada, Adina Magda Florea - "Virtual Patient": An Online Learning Platform for Medical Students, Roundtable on Technology Transfer of Digital Health Solutions in Romania - the Product Pathway from Academic Research to Patient Life, Council Chamber of Faculty of Medicine, University of Medicine and Pharmacy "Carol Davila" Bucharest, Bucharest, Romania, 22 February 2024.

Presentation: Alexandru Scafa-Udriște - Possible applications of artificial intelligence in cardiology, between dream and reality, National Conference Technology & iHealth in Medicine of the XX1st Century, Targu Mures, Romania, 17-19 April 2024.

Articol - Jurnal: Imad Alex Awada, Adina Magda Florea, Alexandru Scafa-Udriște - An e-learning Platform for Clinical Reasoning in Cardiovascular Diseases: A Study Reporting on Learner and Tutor Satisfaction, BMC Medical Education, ISSN: 1472-6920, 2024. (Submitted - Under Evaluation)

Patent of Invention Application: Patent Invention Application submitted to the State Office for Inventions and Trademarks (OSIM registration number: A/00323 from 13 June 2024) - Artificial intelligence-based system for training in the diagnosis and treatment of cardiovascular diseases.

Data Set: Extending the data set which contains data for 7 cardiovascular cases: 5 cases - unique pathology and 2 cases - multiple pathologies.

Virtual Patient Platform: Learning and Diagnostic Platform (public address, platform accessible only to authorized users).


2023

Conference Article: Imad Alex Awada, Alexandru Sorici, Adina Magda Florea, Alexandru Scafa-Udriște - Enhanced Design and Functionalities for the Virtual Patient Educational Platform, 24th International Conference on Control Systems and Computer Science (CSCS 2023), Bucharest, Romania, 24-26 May 2023.

Conference Article: Ana-Maria Simion, Şerban Radu - Experiments with Semi-Supervised Learning: from Cityscapes to Medical Images, 24th International Conference on Control Systems and Computer Science (CSCS 2023), Bucharest, Romania, 24-26 May 2023.

Conference Article: Mohammad Rasras, Iuliana Marin, Şerban Radu - Home Care Assistance Solution Based on a Software Multi-Agents System, 24th International Conference on Control Systems and Computer Science (CSCS 2023), Bucharest, Romania, 24-26 May 2023.

Presentation: Imad Alex Awada, Adina Magda Florea, Alexandru Scafa-Udriște - The Virtual Patient Platform, Interdisciplinary Workshop "Applications of Artificial Intelligence in Medicine", Bucharest, Romania, 30 March 2023.

Panel Discussion: Adina Magda Florea - Project presentation at the event BeHEALTH 2023 (E-Health Panel Discussion) organized by the ROHEALTH cluster, West University of Timisoara, Timisoara, Romania, 24-26 October 2023.

Presentation: Imad Alex Awada, Alexandru Sorici, Adina Magda Florea, Alexandru Scafa-Udriște - The Virtual Patient Platform – A System for Training in Cardiovascular Diseases Diagnostic and Treatment, 11th edition of the Congress of the University of Medicine and Pharmacy "Carol Davila" Bucharest, Parliament House, Bucharest, Romania, 26-28 October 2023.

Data Set: Creation of a data set which contains data for 7 cardiovascular cases: 5 cases - unique pathology and 2 cases - multiple pathologies.


2022

Conference Article: Imad Alex Awada, Alexandru Sorici, Marius Drăgoi, Adina Magda Florea, Alexandru Scafa-Udriște - Virtual Patient: A Web-Based Platform for the Training of Medical Students in Patient Consultation During a Lockdown, 14th Annual International Conference on Education and New Learning Technologies (EDULEARN 2022), Palma de Mallorca, Spain, 4-6 July 2022.

Conference Article: Imad Alex Awada, Alexandru Sorici, Marius Drăgoi, Adina Magda Florea, Alexandru Scafa-Udriște - Virtual Patient: Architecture of an Educational Web Platform for the Assessment of Consultation and Diagnosing Skills of Medical Students, 15th annual International Conference of Education, Research and Innovation (ICERI 2022), Sevilla, Spain, 7-9 November 2022.

Conference Article: Alice Lavinia Chiru, Imad Alex Awada, Alexandru Sorici, Adina Magda Florea, Alexandru Scafa-Udriște - A Support Module for the Virtual Patient Educational Platform, 10th edition of the IEEE International Conference on e-Health and Bioengineering (EHB 2022), Iasi, Romania, 17-19 November 2022.

Presentation: Imad Alex Awada, Alexandru Scafa-Udriște, Adina Magda Florea - Virtual Patient: A Platform that Enables the Remote Training of Medical Students in Patient Consultation, Spring Scientific Conference of the Academy of Romanian Scientists, "The Digital Age – Challenges and Opportunities for Contemporary Society" (AOSR 2022), Bucharest, Romania, 6-7 May 2022.

Presentation: Imad Alex Awada, Adina Magda Florea, Alexandru Scafa-Udriște - Virtual Patient: Student Training in Cardiovascular Diseases Diagnostic and Treatment, The Human Dimension of Artificial Intelligence Workshop, Bucharest, Romania, 22 June 2022.

Promo - Video Material: Presentation of the Virtual Patient project during the conference ITUPP2022. The conference was held in Bucharest, Romania between the 26th of September and 14th of October 2022.

Promo - Video Material: Report about the Virtual Patient project broadcast on Antena 3 on 12 November 2022.

Promo - About the Project

Link to external source (Youtube)

Promo - Antena 3

Link to external source (Youtube)

Promo - ITUPP2022

Link to external source (Youtube)

Short Presentation

Virtual Patient

The project developed an e-learning platform that simulates the interactions between a medical student or resident and a virtual clinical patient for the diagnosis and treatment of acute and chronic cardiovascular diseases. The platform simulates real-life clinical scenarios in which the student plays the role of the doctor who initiates a dialogue with the virtual patient to find out his history, performs an anamnesis and physical examination, requests paraclinical investigations, establishes a diagnosis and recommends a treatement plan. The interface of the virtual patient allows interaction in written and spoken natural language, in Romanian and English. The interaction of the student with the virtual patient can be viewed by the teacher, both synchronously and asynchronously, with the teacher giving notes and feedback for the actions performed by the student.

Data were collected and anonymized for a number of 5 clinical cases for patients with unique conditions, respectively: Pulmonary Thromboembolism, Aortic Stenosis, Myocardial Infarction, Mitral Regurgitation and Cardiac Insufficiency; and a number of 2 clinical cases of patients who have two or more conditions, respectively: the first case in which the patient simultaneously suffers from acute inferior myocardial infarction, severe functional mitral regurgitation and heart failure; and the second case where the patient suffers from heart failure and mitral stenosis simultaneously.

An automatic scenario generation algorithm was developed for the different clinical cases (mentioned earlier), with data consistency checking, and synthetic data were generated to expand the datasets.

The platform was validated with 5 groups of students from UMFCD in several stages, totaling a number of 210 users: 178 students from UMFCD, as direct beneficiaries of the platform, 25 students from UNSTPB to evaluate the technical aspects of the platform (total students 203) and 7 teachers from UMFCD. Feedback was collected from them. The results of the feedback were analyzed and used to improve the functionality and performance of the platform. Students considered the Virtual Patient platform as a significant aid in learning, and teachers shared the same opinion with students.

Virtual Patient
Virtual Patient
Virtual Patient
Virtual Patient
Contact

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Funding

Virtual Patient

This project is funded by the Ministry of Education and Research, CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2021-2511.

UEFISCDI