Scientists of the SI "The Filatov Institute of Eye Diseases and Tissue Therapy of the NAMS of Ukraine", in collaboration with researchers from Nicolae Testemițanu State University of Medicine and Pharmacy (Chișinău, Republic of Moldova) and Grigore T. Popa University of Medicine and Pharmacy (Iași, Romania), have published the results of a joint international study in the Romanian Journal of Ophthalmology.

The authors of the publication from the Filatov Institute are: O.V. Guzun, Candidate of Medical Sciences, Senior Research Fellow at the Department of the Study of the Biological Effects and Application of Lasers in Ophthalmology; O.S. Zadorozhny, Doctor of Medical Sciences, Deputy Director for Scientific Research; A.R. Korol, Doctor of Medical Sciences, Professor, Deputy Director for Innovation and External Relations; L.M. Velychko, Doctor of Medical Sciences, Senior Research Fellow, Head of the Immunology Laboratory.

The article, "Neural Network-Supported Prognostic Assessment of Apoptotic and Inflammatory Markers in Neovascular Glaucoma," presents the results of an interdisciplinary study devoted to the application of current biomarkers and artificial intelligence technologies for predicting the effectiveness of treatment in patients with neovascular glaucoma.

The study evaluated the prognostic value of apoptosis biomarkers (CD95/Fas), endothelial activation biomarkers (CD54/ICAM-1), as well as integrated systemic inflammation indices—SII (Systemic Immune-Inflammation Index), SIRI (Systemic Inflammation Response Index), and AISI (Aggregate Index of Systemic Inflammation). Advanced statistical methods, including regression models and artificial neural network models, were used for the analysis, making it possible to assess the ability of predicting the outcomes of modified selective diode transscleral cyclophotocoagulation.

The obtained results demonstrated that the indicators of apoptosis, endothelial activation, and systemic inflammation are significantly associated with the effectiveness of treatment in patients with neovascular glaucoma. The comprehensive use of these biomarkers together with machine learning algorithms opens up prospects for more accurate individualised prediction of clinical outcomes and risk stratification of patients based on their risk of an adverse disease course.

The study results confirm the significant potential for integrating artificial intelligence technologies into modern clinical ophthalmology. The proposed approach may become an important step toward implementing personalised medicine tools, improving the accuracy of predicting treatment effectiveness, and optimizing the management strategy for patients with neovascular glaucoma.

The publication is the result of international scientific collaboration and confirms the active participation of researchers of the Filatov Institute in the development of current  high-tech areas of ophthalmic science, particularly in the application artificial intelligence methods in medical research and clinical practice.