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    Automatic diagnosis of ureteral stone and degree of hydronephrosis with proposed convolutional neural network, RelieF, and gradient-weighted class activation mapping based deep hybrid model
    (Wiley, 2023) Bugday, Muhammet Serdar; Akcicek, Mehmet; Bingol, Harun; Yildirim, Muhammed
    Urinary system stone disease is a common disease group all over the world. Ureteral stones constitute 20% of all urinary system stones. Ureteral stones are important because they can cause hydronephrosis and related renal parenchymal damage in the kidneys. In the study, a hybrid model was developed to detect hydronephrosis and ureteral stones from kidney images. In the developed model, heat maps of the original images were obtained by using gradient-weighted class activation mapping (Grad-CAM) technology. Then, feature maps were extracted from both the original and heatmap datasets using the Efficientnetb0 architecture. Extracted feature maps were concatenated using a multimodal fusion technique. In this way, different features of an image are obtained. This has a positive effect on the performance of the model. The Relief dimension reduction technique was used to eliminate unnecessary features in the obtained feature map so that the proposed model can work faster and more effectively. Finally, the optimized feature map is classified in the support vector machine (SVM) classifier. To compare the performance of the proposed hybrid model, results were obtained with 8 state-of-the-art models accepted in the literature. Among these models, the highest accuracy value was achieved in the Efficientnetb0 architecture with 67.98%, whereas the accuracy of the proposed hybrid model was 91.1%. This value indicates that the proposed model can be used for HUN diagnosis.
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    The impact of post-earthquake anxiety and depression on erectile dysfunction: A cross-sectional study after the February 6, 2023 Earthquakes in Turkiye
    (Kare Publ, 2026) Bugday, Muhammet Serdar; Akdemir, Ender; Ugur, Kerim; Cakmak, Battal Selcuk; Akbulut, Mehmet Levent; Polat, Hatice
    OBJECTIVE: This study aimed to evaluate the effects of the February 6, 2023, earthquakes in Turkiye on anxiety and depression levels and their impact on erectile dysfunction (ED). METHODS: A total of 164 men aged 25-55 were enrolled between July 15, 2024, and January 15, 2025. Ninety-seven patients who presented with ED after the earthquakes were included as the study group, and 67 healthy individuals without ED were enrolled as controls. All participants completed the Arizona Sexual Experiences Scale (ASEX), Hamilton Anxiety Rating Scale (HAM-A), Hamilton Depression Rating Scale (HAM-D), World Health Organization Quality of Life-BREF (WHO-QOL-BREF), and International Index of Erectile Function (IIEF-5). Statistical analyses were conducted using chi-square, t-tests, and ANOVA. RESULTS: There were no significant differences between the groups regarding age and marital status. Patients with ED had significantly higher ASEX, HAM-A, and HAM-D scores and significantly lower WHOQOL-BREF scores compared to controls (p=0.001). Among ED patients, 52 (53.6%) had severe ED, 40 (41.2%) had moderate, and 5 (5.2%) had mild symptoms. ASEX scores were significantly higher (p=0.01), and WHOQOL-BREF general health scores were significantly lower in patients with severe ED compared to those with milder forms (p=0.001). CONCLUSION: The February 6 earthquakes were associated with increased anxiety and depression and decreased quality of life in men, which significantly contributed to the prevalence and severity of ED. These findings highlight the importance of addressing sexual health as part of post-disaster psychosocial support.