Application of Artificial Intelligence in Otolaryngology Resident Training
09-12, 17:00–18:00 (Europe/Istanbul), Young IFOS 1

<p>Introduction: The traditional Halstedian apprenticeship model ("See one, do one, teach one") is increasingly challenged by ethical constraints, reduced working hours, and significant global disparities in training resources. While young otolaryngologists in major academic centers benefit from high-volume robotic and endoscopic exposure, peers in developing regions often lack access to specialized mentorship. This presentation proposes a paradigm shift: leveraging Artificial Intelligence (AI) and Deep Learning (DL) not merely as diagnostic tools, but as the great equalizer in surgical education.</p> <p>Methods & Analysis: We analyzed scientific studies exploring the growing role of Computer Vision (CV) and Motion Analysis algorithms in Otolaryngology training. Specifically, we examined DL models trained to objectively assess surgical videos of Endoscopic Sinus Surgery (ESS) and temporal bone dissection. These systems were evaluated on their ability to act as "Virtual Mentors," providing automated, granular feedback on instrument handling, tissue respect, and operative flow compared to standard OSATS (Objective Structured Assessment of Technical Skills) scores.</p> <p>Results: Current Deep Learning models demonstrate the capacity to segment surgical phases and identify unsafe maneuvers with accuracy comparable to expert consensus. By integrating these AI-driven feedback loops into cloud-based simulation platforms, residents can achieve proficiency benchmarks independently of their geographic location or local faculty availability. This technology effectively decouples high-quality surgical feedback from the physical presence of a master surgeon.</p> <p>Conclusion: For the Young IFOS community, AI represents a critical opportunity to bridge the global training gap. Transitioning from subjective apprenticeship to data-driven, objective competence assessment fosters true global diversity. By embracing these "Augmented Intelligence" tools, we can ensure that the next generation of otolaryngologists achieves a standardized level of excellence, ensuring that patient safety and surgical skill are defined by dedication, not geography.</p>
<p>This round table session aims to foster a collaborative dialogue on utilizing Deep Learning to standardize surgical training globally. While AI-driven 'Virtual Mentors' offer a solution to mentorship gaps, refining their methodology requires a multi-centric, global perspective. We propose an interactive discussion to critique current DL performance metrics in Otolaryngology and explore how to integrate diverse surgical datasets into these models. Our goal is to exchange ideas with international peers to advance AI-based assessment tools, ensuring they are culturally inclusive, technically robust, and capable of bridging the competency gap between different healthcare ecosystems.</p>
Moderator Moderator
Sermin Can
Speaker Speaker
Resul Arjin Öksüz
Alper Özdemir
Ahmet Furkan Kürüm
Ferhat Deniz
Banu Öksüz Ok
Resul Arjin Öksüz
<p>2009- 2013 Diyarbakır Science High School, Turkey2013 - 2019 Akdeniz University Faculty of Medicine, Turkey (Formal Education)2019-2020 Selahattin-I Eyyubi Hospital (Practicioner)2020-Present Ankara University ORL-HNS DepartmentORL-HNS Speciality Education(5 years)</p> <p>2024- European Board written Exam passed.</p> <p>2025 October to January Fellowship programme accepted from Luzern University ENT Department</p> <p>2024-05-13 to 2024-05-30 | Experimental animal use certificate for the animal group “ rodents ( mouse, rat , guinea pig and rabbit) (Ankara university medicine faculty)</p> <p>2022-06-25 to 2022-06-26 | Hand on dissection (15. Turkish otorhinolaryngology temporal bone dissection course)</p> <p>2025-10-05 to 2025-10-06 | Hands on Dissection Laterall Skull Base Course</p>
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Sermin Can
<p>Medical Degree: Yuzuncu Yıl University Faculty of Medicine, Van, Turkiye, 2002-2008</p> <p>Residency: Inonu University Faculty of Medicine, Otorhinolaryngology and Head and Neck Surgery Department, Malatya, Turkiye, 2010-2014</p> <p>Experience: Dicle University Faculty of Medicine, Otorhinolaryngology and Head and Neck Surgery Department, Diyarbakır, Turkiye, 2022- present</p> <p>Fellow program</p> <p>1) Transoral Laser Surgery and Head and Neck Surgery (as a fellow), in Dışkapı Research and Training Hospital (three months), Ankara, Turkey, 2021</p> <p>2) University Otolaryngology Clinic at San Giovanni Bosco Hospital during the period January 1st → March 31st, (three months), Turin, Italy, 2025</p> <p>Publications</p> <p>1) Can deep learning replace histopathological examinations in the differential diagnosis of cervical lymphadenopathy? Can S, Türk Ö, Ayral M, Kozan G, Arı H, Akdag M, Baylan MY . European Archives of Oto-Rhino-Laryngology (2024) 281:359–367</p> <p>2) Is the Ensemble Machine Learning Model a Reliable Method for Detecting Neoplastic Infiltration of Thyroid Cartilage in Laryngeal Cancers? Can S, Türk Ö, Ayral M, Kozan G, Onur M, Yagız E, Akdag M. Medicina (2025). 61(11), 1945.</p> <p>3) Role of machine learning segmentation method based on CT images in preoperative staging of oral cavity cancer. Can S, Succo G, Coskun C, Korkmaz MH, Akdag M. European Archives of Oto-Rhino-Laryngology (2025). https://doi.org/10.1007/s00405-025-09824-9</p>
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Alper Özdemir
<p>Dr. Alper Özdemir graduated from Hacettepe University Faculty of Medicine in 2022. He is currently pursuing his residency training at the Department of Otolaryngology - Head and Neck Surgery, Ankara Etlik City Hospital</p>
Ahmet Furkan Kürüm
<p>Dr. Kürüm graduated from Hacettepe University Medical School at 2018. He completed his residency at Ankara University ENT-H&N Surgery department and completed his training on April 2025. He is still working as an ENT specialist at Sakarya Training and Research Hospital.</p>
Ferhat Deniz
<p>I am Dr. Ferhat Deniz.I was graduated from Hacettepe University Faculty of Medicine in 2022.I am currently pursuing my residency training at the Department of Otolaryngology - Head and Neck Surgery, Ankara Etlik City Hospital."</p>
Banu Öksüz Ok
<p>I graduated from Hacettepe University Faculty of Medicine in 2022. Currently, I am completing my residency in the Otorhinolaryngology (ENT) department at Ankara Etlik City Hospital. My professional interests are focused on the intersection of technology and medicine, specifically in laryngology and the applications of artificial intelligence in clinical practice. I am dedicated to exploring how AI-driven solutions can enhance diagnostic precision and surgical outcomes in voice and airway disorders.</p>
ilayda Baykan Kendir
<p>I am an Otolaryngology-Head and Neck Surgery resident at Istanbul Bakırköy Dr. Sadi Konuk Training and Research Hospital, one of Turkey's leading tertiary referral centers. Now in my 4th year of residency, ı have gained extensive clinical and surgical experience in a high-volume environment.Attending IFOS 2026, aim to exchange knowledge with global peers and stay at the forefront of the latest advancements in the field.</p>