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Prof. Dr. Kasım Öztoprak, a faculty member in the Department of Computer Engineering at our university, delivered a significant presentation titled "Deep Learning for Assessing Corneal Endothelial Cell Density in Patients After Descemet Membrane Endothelial Keratoplasty" at the Annual Meeting of the American Society of Cataract and Refractive Surgery (ASCRS)

Prof. Dr. Kasım Öztoprak, a faculty member in the Department of Computer Engineering at our university, delivered a significant presentation titled "Deep Learning for Assessing Corneal Endothelial Cell Density in Patients After Descemet Membrane Endothelial Keratoplasty" at the Annual Meeting of the American Society of Cataract and Refractive Surgery (ASCRS)
Paylaş:14.05.2025

Prof. Dr. Kasım Öztoprak, a faculty member in the Department of Computer Engineering at our university, delivered an important presentation titled "Deep Learning for Assessing Corneal Endothelial Cell Density in Patients After Descemet Membrane Endothelial Keratoplasty" at the annual meeting of the American Society of Cataract and Refractive Surgery (ASCRS) annual meeting held in Los Angeles, United States, from April 25–28, 2025, where he delivered an important presentation titled "Deep Learning for Assessing Corneal Endothelial Cell Density in Patients After Descemet Membrane Endothelial Keratoplasty."

Our university’s esteemed faculty member, Prof. Dr. Öztoprak, along with an international research team comprising Prof. Dr. Özlem Evren Kemer, Assoc. Prof. Dr. Emine Esra Karaca, Dr. Feyza Dicle Işık, and Dr. Ayça Bulut Ustael from Ankara Bilkent City Hospital at the University of Health Sciences, and Prof. Dr. Anna Fabijanska from Lodz University of Technology in Poland, presented an innovative study utilizing artificial intelligence and deep learning techniques to assess corneal endothelial cell density.

This study introduces a revolutionary approach to monitoring corneal health, particularly in patients who have undergone Descemet’s Membrane Endothelial Keratoplasty (DMEK) surgery. The developed deep learning model can assess corneal endothelial cell density more quickly and accurately than traditional methods, enabling better monitoring of patients’ recovery processes and facilitating the early detection of complications.

This study represents a significant step in integrating technological innovation into clinical practice in the field of eye health and once again highlights our university’s outstanding achievements in scientific research.

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