With the event organized by the Turkish Society of Microbiology and the TRNC Microbiology Platform, the areas of use of “artificial intelligence” and the applications of mathematical modeling in microbiology and health were discussed.
Areas of use of “artificial intelligence” in microbiology were discussed during the event organized by Turkish Microbiology Society in cooperation with TRNC Microbiology Platform within the framework of webinars. The presentations made by researchers from the Near East University during the event, which took place with the participation of more than 150 medical professionals and microbiologists from Turkey and the TRNC, attracted great attention from the participants.
The TMC-TRNC Microbiology Platform, one of the working groups of the Turkish Microbiology Society, shared information and developments with the microbiology community, including the applications of artificial intelligence technology used everywhere in the world during the pandemic process in the diagnosis of infectious diseases in the TRNC, and the advantages it offers in the field of health.
All aspects of “artificial intelligence” in microbiology were covered
Near East University Faculty of Medicine Lecturer Assoc. Dr. Emrah Ruh and Lecturer’s Assistant of the Faculty of Medicine, Cyprus International University. Assoc. Dr. In the event moderated by Ayşe Seyer; Assoc. Dr. Dilber Uzun Özşahin “Artificial intelligence and its applications in the field of health”; Assoc. Dr. Bilgen Kaymakamzade “Mathematical Models in Medicine”; Assoc. Dr. Ayşe Arıkan Sarıoğlu “A new approach to microbiological diagnosis: multi-criteria decision-making theory”; Assoc. Dr. Meryem Güvenir “Mycobacterium with Artificial Intelligence Model in the Clinical Mycobacteria Laboratory tuberculosis Diagnosis: Preliminary Study Report”; Assoc. Dr Buket Baddal “Can we speed up diagnosis of COVID-19 RT-qPCR using artificial intelligence?” ; Dr. Emrah Guler “Plasmodium spp. He presented his work entitled “The use of artificial intelligence in diagnosis”.
The prevalence of artificial intelligence in the medical field is increasing day by day.
Computer systems based on artificial intelligence have a wide range of uses in the field of medicine. These methods are most commonly used in the diagnosis, treatment, and drug development, as well as in the fight against COVID-19.
Artificial intelligence, with a simple definition, is explained as producing a large amount of data using certain algorithms and solving the problem accordingly. Artificial intelligence-based methods are now finding applications in clinical microbiology as well as in fields such as cardiology, endocrinology, nephrology and gastroenterology. In microbiology, these methods show promise for purposes such as microscopic diagnosis, assessment of growth in culture, prediction of antimicrobial resistance, and strain typing.
teacher. Dr. Tamer Sanlidag: “The application of methods based on artificial intelligence in multidisciplinary studies will open up new horizons in the field of microbiology.”
Acting rector of the Near East University, Professor Tamer Şanlıdağ, said that artificial intelligence-based systems will guide science and these methods can be used for diagnosis of infectious agents in microbiology laboratories clinic in the future. Emphasizing that these methods have also contributed to the control of the COVID-19 epidemic, Prof. Dr. Şanlıdağ said that the increase in cooperation between research centers and the application of methods based on artificial intelligence in multidisciplinary studies will bring an innovative approach in the field of microbiology.
Stating that during the event, mathematical modeling, which is as important as the applications of artificial intelligence, was also discussed. Dr. Şanlıdağ said, “Especially our experience in the COVID-19 process, we have seen that mathematical modeling has yielded revealing results in the surveillance and control of epidemic diseases. During the event, we shared our experiences with the scientific world on the mathematical models we applied to monitor COVID-19 in TRNC.