Akademik Veri Yönetim Sistemi
APPLIED SCIENCES-BASEL, cilt.15, sa.4, 2025 (SCI-Expanded, Scopus)
Cisplatin, a widely used chemotherapeutic agent, is highly effective in treating various cancers, including ovarian and lung cancers, but it often causes ovarian tissue damage and impairs reproductive health. Exosomes derived from mesenchymal stem cells are believed to possess reparative effects on such damage, as suggested by previous studies. This study aims to evaluate the reparative effects of cisplatin and exosome treatments on ovarian tissue damage through the analysis of histopathological images and machine learning (ML)-based classification techniques. Five experimental groups were examined: Control, cisplatin-treated (Cis), exosome-treated (Exo), exosome-before-cisplatin (ExoCis), and cisplatin-before-exosome (CisExo). A set of 177 Local Binary Pattern (LBP) features were extracted from histopathological images, followed by feature selection using Lasso regression. Classification was performed using ML algorithms, including decision tree (DT), k-nearest neighbors (KNN), support vector machine (SVM), and Artificial Neural Network (ANN). The CisExo group exhibited the most homogeneous texture, suggesting effective tissue recovery, whereas the ExoCis group demonstrated greater heterogeneity, possibly indicating incomplete recovery. KNN and ANN classifiers achieved the highest accuracy, particularly in comparisons between the Control and CisExo groups, reaching an accuracy of 87%. The highest classification accuracy was observed for the Control vs. Cis groups (approximately 91%), reflecting distinct features, whereas the Control vs. Exo groups demonstrated lower accuracy (around 68%) due to feature similarity. Exosome treatments, particularly when administered post-cisplatin, significantly improve ovarian tissue recovery. This study highlights the potential of ML-based classification as a robust tool for evaluating therapeutic outcomes. Additionally, it underscores the promise of exosome therapy in mitigating chemotherapy-induced ovarian damage and preserving reproductive health. Further research is warranted to validate these findings and optimize treatment protocols.