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    ARTIFICIAL INTELLIGENCE-ASSISTED PREDICTION OF COVID-19 STATUS BASED ON THORAX CT SCANS USING A PROPOSED META-LEARNING STRATEGY
    (Carbone Editore, 2022) Guldogan, Emek; Yilderim, Ismail Okan; Sevgi, Serkan; Colak, Cemil
    Background: Radiological techniques integrated with artificial intelligence (AI) are a promising diagnostic tool for the rapidly increasing number of COVID-19 cases today. In this study, we intended to construct an artificial intelligence-assisted prediction of COVID-19 status based on thorax computed tomography (CT) scans using a proposed meta-learning strategy. Methods: A public dataset including 1252 positive and 1230 negative thorax CT scans of SARS-CoV-2 was used in the current study. The CT images for COVID-19 status were analyzed by 26 transfer learning (TL) models. The stacking ensemble learning was used to obtain more consistent and high-performance prediction results by combining the prediction results of 26 TL models with an Results: Mobile had the best prediction with an accuracy of 0.946 (95% CI: 0.93-0.962) among the TL models. The Meta-learning model yielded the best classification accuracy of 0.993 (0.98-1), which outperformed MobileNet, the most successful architecture Conclusions: The proposed meta-model that can distinguish CT images between COVID-19 positive and abnormal/normal conditions due to other etiology of COVID-19 negative may be beneficial in such pandemics. The AI application in this study can be used in mobile, desktop, and web-based platforms to have facilitating and complementary effects on classical reporting and the current workload in radiology departments.
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    Morphometric examination of the hepatobiliary duct system in healthy individuals and patients with cholelithiasis: A radio-anatomic magnetic resonance cholangiopancreatography study
    (Cukurova Univ, Fac Medicine, 2023) Toy, Seyma; Senol, Deniz; Ciftci, Rukiye; Sevgi, Serkan; Secgin, Yusuf; Yildirim, Ismail Okan
    Purpose: Cholelithiasis is a common gallbladder disease with high morbidity and treatment cost. Although the disease has many formation factors such as bile duct obstruction, congenital anomalies, genetic and metabolic diseases, the main cause is gallstones. The aim of this study is to examine the radio-anatomic and demographic characteristics of the bile ducts of patients who have cholelithiasis due to gallstones by using magnetic resonance cholangiopancreatography (MRCP) and to compare with healthy individuals.Materials and Methods: The study was carried out by retrospectively scanning the MRCP images of 113 patients diagnosed with cholelithiasis and 87 healthy individuals who were referred to the hospital for various indications and had no gallbladder pathology. Results: According to the Spearman rho correlation test performed by ignoring gender, a significant correlation was found between right hepatic duct diameter (RHD-D) and right hepatic duct - cystic duct angle (RHDCD-A), and between left hepatic duct diameter (LHD-D) and common bile duct diameter (CBD-D). In the correlation analysis performed only among males, a significant correlation was found between RHDCD-A and right hepatic duct - left hepatic duct angle (RLHD-A), RHDCD-A and common hepatic duct diameter (CHD-D) parameters. In the correlation analysis performed only among women, a significant relationship was found between age and RHD-D, LHD-D, CHD-D, CBD-D, between RHDCD-A and cystic duct - gallbladder angle (CDG-A), RHD-D, and between CHD-D and cystic duct diameter (CD-D).Conclusion: This study will contribute to literature by revealing the morphometric characteristics and radio -anatomic information of the hepatobiliary systems of both patients with cholelithiasis and healthy individuals.