Publications by authors named "F Durmaz"
Deep learning in distinguishing pulmonary nodules as benign and malignant.
Turk Gogus Kalp Damar Cerrahisi Derg
July 2024
Article Synopsis
- - The study aimed to improve early lung cancer diagnosis by developing convolutional neural network models to accurately differentiate between benign and malignant lung nodules using diagnostic imaging data from 2015 to 2020.
- - Patients were categorized into three groups—benign, malignant, and control—while deep neural networks were trained on 80% of their data and tested on the remaining 20%, showing an accuracy of up to 80% with AlexNET and 93.5% when using a support vector machine classifier with the VGG19 model.
- - The findings indicate that utilizing deep learning and feature extraction effectively enhances the ability to identify lung nodules, supporting early diagnosis and potentially improving radiology practices.
Background: Although there have been significant improvements in the treatment of heart failure (HF) in recent decades, its prognosis remains poor. Although there are many biomarkers that can help predict the prognosis of patients with HF, there is a need for simpler, cheaper, and more easily available biomarkers.
Objective: To evaluate the predictive value of pan-immune-inflammation value (PIV) in patients with acute decompensated HF.
Doubling time in pulmonary and hepatic hydatid cysts.
Turk Gogus Kalp Damar Cerrahisi Derg
April 2024
Background: This study aims to investigate whether the concept of doubling time in hydatid cysts differs according to different parameters such as age, sex, and whether the cyst is located in the lung or liver. Background: This study aims to investigate whether the concept of doubling time in hydatid cysts differs according to different parameters such as age, sex, and whether the cyst is located in the lung or liver.
Methods: Between January 2012 and August 2023, a total of 138 hydatid cysts were retrospectively analyzed.
Purpose: This study is to investigate the effectiveness of Acoustic Radiation Force Impulse (ARFI) elastography in differentiating radiologically similar renal cell carcinoma (RCC) and oncocytoma in solid masses of the kidney.
Methods: The patients with solid renal mass histopathological diagnosed after excision or tru-cat biopsy who underwent a preoperative ARFI elastography of the lesion during a 4-year period were included in this study. Preoperative shear wave velocity (SWV) values were measured in all the lesions.