2025 Yılı Web of Science Başarısı

2025 yılında, bölümümüz akademik personelinin katkı sunduğu ve Web of Science (WOS) tarafından SCI/SCI-E kategorilerinde indekslenen toplam 7 makale yayımlanmıştır. Bu değerli katkılarından dolayı akademik personelimize teşekkür eder, çalışmalarında başarılarının devamını dileriz.

BİYOMEDİKAL MÜHENDİSLİĞİ BÖLÜM BAŞKANLIĞI

1. Altunkaya, S., Özmen, G., & Babur, E. (2025). Investigating Neural Dynamics in Tinnitus Using Constrained Independent Component Analysis. Brain Connectivity, 15(7), 263–277. https://doi.org/10.1177/21580014251362839

2. Bascil, M. S., & Iscanli, I. N. (2025). An Innovative Approach for Extraction of Smoking Addiction Levels Using Physiological Parameters Based on Machine Learning: Proof of Concept. Diagnostics, 15(22), 2839. https://doi.org/10.3390/diagnostics15222839

3. Bascil, M. S. (2025). A novel data mining approach for early diagnosis of gestational diabetes mellitus (GDM) in pregnancy via machine learning methods and CNN. Acta of Bioengineering and Biomechanics, 27(2). https://doi.org/10.37190/abb/209528

4. Erharman, A., Okutan, K., Dogan, E. E., & Aydin, B. (2025). A transcriptomics-guided network pharmacology and structure-based modeling framework reveals molecular signatures and multi-target repurposed therapeutics for COVID-19. Network Modeling Analysis in Health Informatics and Bioinformatics, 15(3). https://doi.org/10.1007/s13721-025-00688-x

5. Gülhan, P. G., & Özmen, G. (2025). Enhancing Signal and Network Integrity: Evaluating BCG Artifact Removal Techniques in Simultaneous EEG-fMRI Data. Sensors, 25(22), 7036. https://doi.org/10.3390/s25227036

6. Gülhan, P. G., & Özmen, G. (2025). The Use of fMRI Regional Analysis to Automatically Detect ADHD Through a 3D CNN-Based Approach. Journal of Imaging Informatics in Medicine, 38, 203–216. https://doi.org/10.1007/s10278-024-01189-5

7. Incekara, H., Cizmeci, I. H., Saritas, M. M., & Koklu, M. (2025). Classification of almond kernels with optuna hyper-parameter optimization using machine learning methods. Journal of Food Science and Technology. https://doi.org/10.1007/s13197-025-06494-7