National Health and Innovation Symposium
National Health and Innovation Symposium was held online by Turkish Society of Cardiology Digital Health Project Group on June 4 – 5, 2022. At the opening speech of symposium, which was supported with the theme of artificial intelligence in developing health sciences and technologies by Türkiye Health Data Research and Artificial Intelligence Applications Institute (TÜYZE), President of TÜSEB Prof. Dr. Erhan Akdoğan delivered a speech titled “Artificial Intelligence based Health Technologies and Role of TÜSEB”. On the first day of the symposium, the session titled “Artificial Intelligence in Health Studies” was headed by Director of TÜYZE Prof. Dr. Songül Varlı.
On the second day, TKD-TÜSEB/TÜYZE held a joint session in Türkiye Health Data Research and Artificial Intelligence Applications Institute (TÜYZE) organization.
In the session titled “Solutions of Machine Learning in Cardiology” moderated by Director of TÜYZE Prof. Dr. Songül Varlı, Assoc. Prof. Oğuz Akbilgiç from Epidemiological Cardiology Research Centre (EPICARE), Wake Forest School of Medicine delivered a presentation titled “EKG-YZ: Electrocardiographic Artificial Intelligence Model”, and shared his experiences on the usage areas of artificial intelligence for EKG devices, which are the primary finding indicator tool of the cardiology discipline. Another speaker of the session is Prof. Dr. Alex Frangi, from Centre for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), Leeds University, who delivered a presentation titled “Prediction of Heart Attack Risk via Eye Scanning”. He also highlighted the importance of eye movements of patients in terms of heart attack. Dr. Frangi informed participants about his study on determining whether the patient has a heart attack by combining eye movement tracking with artificial intelligence models. At the last speech of the session, Assoc. Prof. İlkay Öksüz from Computer Engineering Dept, İstanbul Technical University delivered a presentation titled “Detection and Correction of Problems of Cardiac MR Images’ Quality via Deep Learning” and shared information on deep learning-based approaches they developed to solve the quality differences caused by the device, patient movements, and shooting specialist etc in magnetic resonance images, which is another examination applied in terms of the cardiology discipline.
Prof. Dr. Varlı ended the session by highlighting that the need for artificial intelligence applications will gradually increase in studies to be carried out in the field of health and cardiology, and the need for physician-engineer cooperation.
