Omar Karadaghy, MD, MSCI

Dr. Omar Karadaghy began his medical training in 2011 through the accelerated B.A./M.D. program at the University of Missouri–Kansas City. From 2016 to 2017, he completed the NIH-funded TL1 Predoctoral Clinical Research Training Program at Washington University in St. Louis. During this dedicated research year, he conducted full-time clinical research while completing the coursework required for a Master of Science in Clinical Investigation.

Dr. Karadaghy subsequently returned to medical school and earned both his Bachelor of Arts in Liberal Arts and Doctor of Medicine degrees in 2018. He then completed his residency in Otolaryngology–Head and Neck Surgery at the University of Kansas from 2018 to 2023. During residency, he further developed his interest in emerging technologies by spearheading an adjunct curriculum in machine learning and artificial intelligence. As part of this work, he completed a machine learning certification through Stanford Online in 2020.

Following residency, Dr. Karadaghy pursued advanced fellowship training in Head and Neck Oncology and Microvascular Reconstruction through the Massachusetts Eye and Ear–Harvard program. There, he refined his expertise in complex oncologic surgery and advanced head and neck reconstruction.

Dr. Karadaghy is committed to delivering comprehensive, patient-centered care. His clinical expertise encompasses the full spectrum of head and neck oncology, including tumors of the thyroid, upper aerodigestive tract, and skull base. He also specializes in complex head and neck reconstruction for defects resulting from cancer, trauma, and infection.

Dr. Karadaghy offers a broad range of advanced surgical treatments, including minimally invasive robotic approaches for tumors in anatomically challenging locations. He works closely with the multidisciplinary oncology teams at The University of Kansas Cancer Center and KU Medical Center to develop individualized treatment plans that integrate surgical care with the full range of cancer services.

Dr. Omar Karadaghy’s research expertise is grounded in clinical outcomes research, with a particular emphasis on improving the treatment and quality of life of patients with head and neck cancer. From June 2016 through May 2017, he pursued a Master of Science in Clinical Investigation, developing a strong foundation in the design, execution, and analysis of rigorous clinical studies. He applied this training extensively during residency, leading and contributing to numerous research projects focused on optimizing patient management and advancing the understanding of disease processes. A significant component of his early work involved exploring the integration of machine learning into otolaryngology at a time when its application within the field was still emerging.

During fellowship, Dr. Karadaghy expanded his research program to include robotic surgery and human papillomavirus–positive head and neck cancer. His work examined surgical techniques and treatment strategies designed to maintain oncologic control while minimizing treatment-related morbidity. In particular, he investigated surgical margin assessment and its implications for the management of HPV-positive disease. This work reflects his broader commitment to advancing head and neck surgery through clinically meaningful research, technological innovation, and thoughtful refinement of treatment paradigms.

Dr. Karadaghy remains actively engaged in clinical research evaluating emerging technologies and management strategies intended to improve cancer outcomes and preserve patients’ quality of life. He is an active member of the American Academy of Otolaryngology–Head and Neck Surgery and the American Head and Neck Society, where he regularly presents his research and collaborates with colleagues from across the country.

Development and Assessment of a Machine Learning Model to Help Predict Survival Among Patients With Oral Squamous Cell Carcinoma.

Development and Validation of Machine Learning Models for Predicting Occult Nodal Metastasis in Early-Stage Oral Cavity Squamous Cell Carcinoma

Development of a New Clinical Severity Staging System for Patients With Nonmetastatic Papillary Thyroid Carcinoma.

Machine learning directed sentinel lymph node biopsy in cutaneous head and neck melanoma.

Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma

Machine Learning to Predict Treatment in Oropharyngeal Squamous Cell Carcinoma.

Prognostic significance of hemorrhage requiring embolization in the setting of previously treated head and neck squamous cell carcinoma: Systematic review and retrospective cohort.

Rates of bone reabsorption and union in mandibular reconstruction using the osteocutaneous radial forearm free flap.

Reporting of Effect Size and Confidence Intervals in JAMA Otolaryngology-Head & Neck Surgery.

Survival for HPV-positive oropharyngeal squamous cell carcinoma with surgical versus non-surgical treatment approach: A systematic review and meta-analysis.