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Öğe 256 kesitli çift tüplü bilgisayarlı tomografi cihazında prospektif EKG tetiklemeli ve retrospektif EKG kapılamalı teknikle çekilen koroner BT anjiografi ıncelemelerinde radyasyon dozu karşılaştırması(2016) Görmeli, Cemile Ayşe; Kahraman, Aysegul Sagir; Özdemir, Zeynep Maraş; Yağmur, Jülide; Özdemir, Ramazan; Açıkgöz, Nusret; Çolak, CemilGiriş: Koroner arter hastalığı, aterosklerotik plakların meydana getirdiği, önemli mortalite ve morbiditeye sahip sık görülen kardiyovasküler bir hastalıktır. Bilgisayarlı tomografi ile koroner anjiografi tetkiki giderek artan sıklıkta invaziv kateter anjiografi yerine kullanılmaya başlanmıştır. Biz de bu çalışmamız ile koroner arter hastalıklarının değerlendirilmesi için bilgisayarlı tomografi kullanılarak prospektif EKG tetiklemeli ve retrospektif EKG kapılamalıteknikle çekilen koroner anjiografi incelemelerinde efektif radyasyon dozlarını saptamayı amaçladık. Gereç ve Yöntemler: 256 kesitli çift tüplü bilgisayarlı tomografi cihazı ile koroner anjiografi çekilen 326 hasta değerlendirildi. Çalışmamızda, hastaların kalp hızına bağlı olarak 3 farklı çekim tekniği kullanarak teknikler arasındaki efektif radyasyon dozunu karşılaştırdık. Bulgular: Teknik I ile çekilen 195 hastanın kalp hızı ortalama 96,1 atım/dk, teknik II ile yapılan 103 incelemede kalp hızı ortalama 80,7 atım/dk, teknik III ile yapılan 28 görüntülemede ise kalp hızı ortalama 57,1 atım/dk olarak saptandı. Ayrıca, ortalama efektif radyasyon dozları; teknik I ile 1,15 mSv, teknik II ile 3,98 mSv ve teknik III ile 10 mSv olarak hesaplandı. Sonuç: Prospektif EKG tetiklemeli teknikle bilgisayarlı tomografi kullanılarak çekilen koroner anjiografi, retrospektif EKG kapılamalı teknikle karşılaştırıldığında düşük efektif radyasyon dozuna neden olmaktadır. Düşük radyasyon dozunda ve optimal görüntü kalitesinde incelemeler elde etmek için, çekim hastanın kalp hızına bağlı olarak en uygun teknik belirlenerek yapılmalıdır.Öğe The acute effect of humic acid on iron accumulation in rats(Biological Trace Element Research, 2016) Çağın, Yasir Furkan; Şahin, Nurhan; Polat, Alaadin; Erdoğan, Mehmet Ali; Atayan, Yahya; Eyol, Ergül; Bilgiç, Yılmaz; Seçkin, Yüksel; Çolak, CemilAbstract Free iron leads to the formation of pro-oxidant reactive oxygen species (ROS). Humic acids (HAs) enhance permeability of cellular wall and act as a chelator through electron transferring. This study was designed to test chelator effect of HA on iron as well as its anti-oxidant effect against the iron-induced hepatotoxicity and cardiotoxicity. The rats used were randomly divided into four groups (n = 8/group): group I (the control group); group II (the HA group), humic acid (562 mg/kg) was given over 10 days by oral gavage; group III (the iron group), iron III hydroxide polymaltose (250 mg/kg) was given over 10 days by intraperitoneal route; and group IV (the HA plus iron group), received the iron (similar to group II) plus humic acid (similar to those in groups II and III) group. Blood and two tissue samples both from liver and heart were obtained for biochemical and histopathological evaluations. Iron deposition, the iron-induced hepatotoxicity, and cardiotoxicity were demonstrated by histopathological and biochemical manner. However, no significant differences were observed in the serum biochemical values and thehistopathological results among the iron and the HA plus iron groups in the liver tissue but not in the heart tissue. The protective effects of humic acid against iron-induced cardiotoxicity were shown but not against hepatotoxicity in our study.Öğe The acute effect of humic acid on ıron accumulation in rats(Biological Trace Element Research, 2016) Çağın, Yasir Furkan; Şahin, Nurhan; Polat, Alaadin; Erdoğan, Mehmet Ali; Atayan, Yahya; Eyol, Ergül; Bilgiç, Yılmaz; Seçkin, Yüksel; Çolak, CemilFree iron leads to the formation of pro-oxidant reactive oxygen species (ROS). Humic acids (HAs) enhance permeability of cellular wall and act as a chelator through electron transferring. This study was designed to test chelator effect of HA on iron as well as its anti-oxidant effect against the iron-induced hepatotoxicity and cardiotoxicity. The rats used were randomly divided into four groups (n = 8/group): group I (the control group); group II (the HA group), humic acid (562 mg/kg) was given over 10 days by oral gavage; group III (the iron group), iron III hydroxide polymaltose (250 mg/kg) was given over 10 days by intraperitoneal route; and group IV (the HA plus iron group), received the iron (similar to group II) plus humic acid (similar to those in groups II and III) group. Blood and two tissue samples both from liver and heart were obtained for biochemical and histopathological evaluations. Iron deposition, the iron-induced hepatotoxicity, and cardiotoxicity were demonstrated by histopathological and biochemical manner. However, no significant differences were observed in the serum biochemical values and the histopathological results among the iron and the HA plus iron groups in the liver tissue but not in the heart tissue. The protective effects of humic acid against iron-induced cardiotoxicity were shown but not against hepatotoxicity in our study.Öğe Adenosine deaminase level in the serum of the patients Toxoplasma gondiiseropositive and Giardia intestinalis(African Journal of Microbiology Research, 2009) Karaman, Ülkü; Beytur, Leyla; Kıran, Tuba; Çolak, CemilAdenosine deaminase (ADA) is an aminohydrolase making adenosine, deoksiadenozini inozin, and deocsiniozine deaminise irreversibly and plays role in the catabolism of purine nucleotids. Toxoplasma gondii is a zoonoses intracellular parasite that causes infection in animals and humans. This parasite encompasses enzymes that produce free radicals such as superoxide and hydrogen peroxide. In addition, Giardia intestinalis is another parasite that causes irritations in mucosa, over mucus discharge, aggravating former inflammations, and various absorption defects. In the present study, it has been aimed to compare ADA levels between T. gondii seropositive (IgG seropositive but symptomless patients), G. intestinalis positive patients, and control group. Thus, ADA levels between 32 patients being T. gondii seropositive and 29 controls and between 50 patients’ G. intestinalis positive and 40 controls have been evaluated. The results were analyzed using independent samples t-test at the level of p < 0.05. According to this, in the statistical comparison between the parameters of patient and control groups, a meaningful decrease could be determined in ADA levels. This situation can be commented in the way that toxoplasmosis infection being inactive does not necessarily cause an increase in T lymphocytes. In addition, this decrease can be due to increasing oxidative stress in parasitic infections. Adenosine deaminase level in the serum of the patients Toxoplasma gondii seropositive and Giardia intestinalis (PDF Download Available). Available from: https://www.researchgate.net/publication/228360278_Adenosine_deaminase_level_in_the_serum_of_the_patients_Toxoplasma_gondii_seropositive_and_Giardia_intestinalis [accessed Jan 16 2018].Öğe Adenosine deaminase level in the serum of the patients Toxoplasma gondiiseropositive and Giardia intestinalis(Afrıcan journal of mıcrobıology research, 2009) Karaman, Ülkü; Beytur, Leyla; Kıran, Tuğba Raika; Çolak, CemilAdenosine deaminase (ADA) is an aminohydrolase making adenosine, deoksiadenozini inozin, and deocsiniozine deaminise irreversibly and plays role in the catabolism of purine nucleotids. Toxoplasma gondii is a zoonoses intracellular parasite that causes infection in animals and humans. This parasite encompasses enzymes that produce free radicals such as superoxide and hydrogen peroxide. In addition, Giardia intestinalis is another parasite that causes irritations in mucosa, over mucus discharge, aggravating former inflammations, and various absorption defects. In the present study, it has been aimed to compare ADA levels between T. gondii seropositive (IgG seropositive but symptomless patients), G. intestinalis positive patients, and control group. Thus, ADA levels between 32 patients being T. gondii seropositive and 29 controls and between 50 patients’ G. intestinalis positive and 40 controls have been evaluated. The results were analyzed using independent samples t-test at the level of p < 0.05. According to this, in the statistical comparison between the parameters of patient and control groups, a meaningful decrease could be determined in ADA levels. This situation can be commented in the way that toxoplasmosis infection being inactive does not necessarily cause an increase in T lymphocytes. In addition, this decrease can be due to increasing oxidative stress in parasitic infections.Öğe Application of knowledge discovery process on the prediction of stroke(Computer Methods and Programs in Biomedicine, 2015) Çolak, Cemil; Karaman, Esra; Turtay, M. GökhanObjective: Stroke is a prominent life-threatening disease in the world. The current study was performed to predict the outcome of stroke using knowledge discovery process (KDP) methods, artificial neural networks (ANN) and support vector machine (SVM) models. Materials and methods: The records of 297 (130 sick and 167 healthy) individuals were acquired from the databases of the department of emergency medicine. Nine predictors (coronary artery disease, diabetes mellitus, hypertension, history of cerebrovascular disease, atrial fibrillation, smoking, the findings of carotid Doppler ultrasonography [normal, plaque, plaque + stenosis ≥ 50%], the levels of cholesterol and C-reactive protein) were used for predicting the stroke. Feature selection based on the Cramer’s V test was carried outfor reducing the predictors. Multilayer perceptron (MLP) ANN and SVM with radial basis function (RBF) kernel were used for the prediction based on the selected predictors. Results: The accuracy values were 81.82% for ANN and 80.38% for SVM in the training dataset (n = 209), and 85.9% for ANN and 84.62% for SVM in the testing dataset (n = 78), respectively. ANN and SVM models yielded area under curve (AUC) values of 0.905 and 0.899 in the training dataset, and 0.928 and 0.91 in the testing dataset, consecutively. Conclusion: The findings of the current study pointed out that ANN had more predictive performance when compared with SVM in predicting stroke. The proposed ANN model would be useful when making clinical decisions regarding stroke.Öğe Application of knowledge discovery process on the prediction of stroke(Computer Methods and Programs in Biomedicine, 2015) Çolak, Cemil; Karaman, Esra; Turtay, Muhammet GökhanObjective: Stroke is a prominent life-threatening disease in the world. The current study was performed to predict the outcome of stroke using knowledge discovery process (KDP) methods, artificial neural networks (ANN) and support vector machine (SVM) models. Materials and methods: The records of 297 (130 sick and 167 healthy) individuals were acquired from the databases of the department of emergency medicine. Nine predictors (coronary artery disease, diabetes mellitus, hypertension, history of cerebrovascular disease, atrial fibrillation, smoking, the findings of carotid Doppler ultrasonography [normal, plaque, plaque + stenosis ≥ 50%], the levels of cholesterol and C-reactive protein) were used for predicting the stroke. Feature selection based on the Cramer’s V test was carried outfor reducing the predictors. Multilayer perceptron (MLP) ANN and SVM with radial basis function (RBF) kernel were used for the prediction based on the selected predictors. Results: The accuracy values were 81.82% for ANN and 80.38% for SVM in the training dataset (n = 209), and 85.9% for ANN and 84.62% for SVM in the testing dataset (n = 78), respectively. ANN and SVM models yielded area under curve (AUC) values of 0.905 and 0.899 in the training dataset, and 0.928 and 0.91 in the testing dataset, consecutively. Conclusion: The findings of the current study pointed out that ANN had more predictive performance when compared with SVM in predicting stroke. The proposed ANN model would be useful when making clinical decisions regarding strokeÖğe Application of medical data mining on the prediction of apache II score(Medicine Science | International Medical Journal, 2015) Çolak, Cemil; Aydoğan, Mustafa Said; Arslan, Ahmet Kadir; Yücel, AytaçThe Acute Physiology and Chronic Health Evaluation (APACHE II) is a beneficial tool for the estimation of risk and the comparison of the patients who received care with similar risk properties. Machine learning based systems can assist clinicians in the early diagnosis of diseases. This research aimed at predicting the APACHE II score using Support Vector Machine (SVM) from Medical Data Mining (MDM). The records of 280 patients from intensive care unit included the dataset containing the target variable (the APACHE II score), and 23 demographical/clinical predictor variables. Genetic algorithm based feature selection and 10-fold cross validation method were employed. SVM with radial basis (RBF) was constructed. The performance of the proposed approach was assessed using root mean squared error (RMSE), mean absolute error (MAE), correlation (R) and coefficient of determination (R2). Mean age of the individuals was 51±23 years. 153 (54.6%) were females, and 127 (45.4%) were males. The proposed approach yielded the values of 1.037 for RMSE, 0.727 for MAE, 0.993 for R and 0.986 for R2, respectively. The results demonstrated that the proposed approach had an excellent predictive performance of the APACHE II score. Additionally, ensemble approaches such as bagging, boosting, voting etc. can improve markedly the performance of the prediction and classification tasks.Öğe Application of Medical Data Mining on the Prediction of APACHE II Score(2015) Çolak, Cemil; Aydoğan, Mustafa Said; Arslan, Ahmet Kadir; Yücel, AytaçThe Acute Physiology and Chronic Health Evaluation (APACHE II) is a beneficial tool for the estimation of risk and the comparison of the patients who received care with similar risk properties. Machine learning based systems can assist clinicians in the early diagnosis of diseases. This research aimed at predicting the APACHE II score using Support Vector Machine (SVM) from Medical Data Mining (MDM). The records of 280 patients from intensive care unit included the dataset containing the target variable (the APACHE II score), and 23 demographical/clinical predictor variables. Genetic algorithm based feature selection and 10-fold cross validation method were employed. SVM with radial basis (RBF) was constructed. The performance of the proposed approach was assessed using root mean squared error (RMSE), mean absolute error (MAE), correlation (R) and coefficient of determination (R2). Mean age of the individuals was 51±23 years. 153 (54.6%) were females, and 127 (45.4%) were males. The proposed approach yielded the values of 1.037 for RMSE, 0.727 for MAE, 0.993 for R and 0.986 for R, respectively. The results demonstrated that the proposed approach had an excellent predictive performance of the APACHE II score. Additionally, ensemble approaches such as bagging, boosting, voting etc. can improve markedly the performance of the prediction and classification tasks.Öğe Application of medical data mining on the prediction of apache ıı score(Medicine Science | International Medical Journal, 2015) Çolak, Cemil; Aydogan, Mustafa Said; Arslan, Ahmet Kadir; Yücel, AytaçThe Acute Physiology and Chronic Health Evaluation (APACHE II) is a beneficial tool for the estimation of risk and the comparison of the patients who received care with similar risk properties. Machine learning based systems can assist clinicians in the early diagnosis of diseases. This research aimed at predicting the APACHE II score using Support Vector Machine (SVM) from Medical Data Mining (MDM). The records of 280 patients from intensive care unit included the dataset containing the target variable (the APACHE II score), and 23 demographical/clinical predictor variables. Genetic algorithm based feature selection and 10-fold cross validation method were employed. SVM with radial basis (RBF) was constructed. The performance of the proposed approach was assessed using root mean squared error (RMSE), mean absolute error (MAE), correlation (R) and coefficient of determination (R2 ). Mean age of the individuals was 51±23 years. 153 (54.6%) were females, and 127 (45.4%) were males. The proposed approach yielded the values of 1.037 for RMSE, 0.727 for MAE, 0.993 for R and 0.986 for R2 , respectively. The results demonstrated that the proposed approach had an excellent predictive performance of the APACHE II score. Additionally, ensemble approaches such as bagging, boosting, voting etc. can improve markedly the performance of the prediction and classification tasks.Öğe Artificial Intelligence Based Video Processing Methods forPredicting COVID-19: Observational Study(2022) Yağın, Burak; Güldoğan, Emek; Çolak, CemilObjective: The aim of this study is to develop a high-performance model and web-based clinical decision making method to successfully distinguish and classify COVID19 from bacterial pneumonia, viral pneumonia and healthy controls with lung ultrasound (LUS) videos using appropriate video processing techniques and artificial intelligence (AI) methods development of the support system. Material and Methods: In this study, the open source LUS video dataset at https://github.com/jannisborn/covid19_ultrasound was used. The dataset includes 32 healthy controls, 24 COVID-19, 24 bacterial pneumonia and 12 viral pneumonia class videos. In the video processing stage, 300 image frames were taken from the videos in each class. The images were divided into 80% (960) training and 20% (240) test datasets. In the modeling phase, the convolutional neural network (CNN) method, one of the deep neural network architectures in the keras library, was used. Accuracy, sensitivity, specificity, precision, Matthews’ correlation coefficient and F1 score criteria are given to evaluate the performance of the model. A web-based system has been developed that can successfully detect COVID-19 using the, with the help of the AI-based model, Python Flask Library. Results: The accuracy in the test dataset was calculated as 93.39% for healthy control, COVID-19 and viral pneumonia, and 95.07% for bacterial pneumonia. Conclusion: According to the performance criteria values obtained with the video processing-based CNN model, it can be said that the developed system gives very successful predictions in the diagnosis of COVID-19, bacterial pneumonia and viral pneumonia.Öğe Assessment of Association Rule Mining Using Interest Measures on the Gene Data(2022) Akbaş, Kübra Elif; Kıvrak, Mehmet; Arslan, Ahmet Kadir; Yakınbas, Tuğçe; Korkmaz, Hasan; Onalan, Ebru; Çolak, CemilAim: Data mining is the discovery process of beneficial information, not revealed from large-scale data beforehand. One of the fields in which data mining is widely used is health. With data mining, the diagnosis and treatment of the disease and the risk factors affecting the disease can be determined quickly. Association rules are one of the data mining techniques. The aim of this study is to determine patient profiles by obtaining strong association rules with the apriori algorithm, which is one of the association rule algorithms. Material and Method: The data set used in the study consists of 205 acute myocardial infarction (AMI) patients. The patients have also carried the genotype of the FNDC5 (rs3480, rs726344, rs16835198) polymorphisms. Support and confidence measures are used to evaluate the rules obtained in the Apriori algorithm. The rules obtained by these measures are correct but not strong. Therefore, interest measures are used, besides two basic measures, with the aim of obtaining stronger rules. In this study For reaching stronger rules, interest measures lift, conviction, certainty factor, cosine, phi and mutual information are applied. Results: In this study, 108 rules were obtained. The proposed interest measures were implemented to reach stronger rules and as a result 29 of the rules were qualified as strong. Conclusion: As a result, stronger rules have been obtained with the use of interest measures in the clinical decision making process. Thanks to the strong rules obtained, it will facilitate the patient profile determination and clinical decision-making process of AMI patients.Öğe Assessment of clinical and pathological features of patients who underwent thyroid surgery: A retrospective clinical study(BAISHIDENG PUBLISHING GROUP INC, 8226 REGENCY DR, PLEASANTON, CA 94588 USA, 2018) Akbulut, Sami; Çolak, CemilTo evaluate whether there was any correlation between the clinical parameters and final pathological results among patients who underwent thyroid surgery. METHODS We retrospectively analyzed parameters, including age, sex, complete blood cell count parameters, nodule diameter, nodule localization, thyroid function testing, and pathology reports, in patients who underwent thyroid surgery. The patients were divided into malignant (n = 92) and benign (n = 413) groups depending on the final pathological results. Both groups were compared for demographic and clinical parameters. The Kolmogorov-Smirnov normality test was used to determine if the quantitative variables had a normal distribution. The nonparametric Mann-Whitney U test was used to compare quantitative data that were not normally distributed, and Pearson's chi-squared test was used to compare the qualitative data. The correlation between the final pathological results and fine-needle aspiration biopsy findings was calculated using the cross-tabulation method. RESULTS This study included 406 women and 99 men aged between 15 and 85 years. No significant differences were found between the groups with respect to age, sex, white blood cell count, neutrophil count, lymphocyte count, thrombocyte count, red cell distribution width, platelet distribution width, mean platelet volume, platecrit, nodule localization, and thyroid function testing. On the other hand, there were significant differences between the groups with respect to nodule size (P = 0.001), cervical lymphadenopathy (P = 0.0001) and nodular calcification (P = 0.0001). Compared with the malignant group, the benign group had a significantly greater nodule size (35.4 mm vs 27.6 mm). The best cut-off point (<= 28 mm) for nodule size, as determined by the receiver operating characteristic curve, had a sensitivity and specificity of 67.7% and 64.4%, respectively. The correlation between fine-needle aspiration biopsy and the final pathological results was assessed using the cross-table method. The sensitivity and specificity of fine-needle aspiration biopsy were 60% and 98%, respectively. CONCLUSION This study showed that significant differences existed between the malignant and benign groups with regard to nodule size, cervical lymphadenopathy, and nodular calcification.Öğe Assessment of myocardial changes in athletes with native T1 mapping and cardiac functional evaluation using 3 T MRI(The International Journal of Cardiovascular Imaging, 2016) Görmeli, Cemile Ayşe; Görmeli, Gökay; Yağmur, Jülide; Özdemir, Zeynep; Kahraman, Ayşegül; Çolak, Cemil; Özdemir, RamazanIntensive physical exercise leads to increases in left ventricular muscle mass and wall thickness. Cardiac magnetic resonance imaging allows the assessment of functional and morphological changes in an athlete’s heart. In addition, a native T1 mapping technique has been suggested as a non-contrast method to detect myocardial fibrosis. The aim of this study was to show the correlation between athletes’ cardiac modifications and myocardial fibrosis with a native T1 mapping technique. A total of 41 healthy non-athletic control subjects and 46 athletes underwent CMR imaging. After the functional and morphological assessments, native T1 mapping was performed in all subjects using 3.0 T magnetic resonance imaging. Most of the CMR findings were significantly higher in athletes who had C5 years of sports activity when compared with non-athletic controls and athletes who had \5 years of sports activity. Significantly higher results were shown in native T1 values in athletes who had \5 years of sports activity, but there were no significant differences in the left ventricular end-diastolic volume, left ventricular end-diastolic mass, or interventricular septal wall thickness between non-athletic controls and athleteswho had \5 years of sports activity. The native T1 mapping technique has the potential to discriminate myocardial fibrotic changes in athletes when compared to a normal myocardium. The T1 mapping method might be a feasible technique to evaluate athletes because it does not involve contrast, is non-invasive and allows for easy evaluation of myocardial remodeling.Öğe Assessment of myocardial changes in athletes with native T1 mapping and cardiac functional evaluation using 3 T MRI(The International Journal of Cardiovascular Imaging, 2016) Görmeli, Cemile Ayşe; Görmeli, Gökhan; Yağmur, Jülide; Özdemir, Zeynep Maraş; Kahraman, Ayşegül Sağır; Çolak, Cemil; Özdemir, RamazanAbstract Intensive physical exercise leads to increases in left ventricular muscle mass and wall thickness. Cardiac magnetic resonance imaging allows the assessment of functional and morphological changes in an athlete’s heart. In addition, a native T1 mapping technique has been suggested as a non-contrast method to detect myocardial fibrosis. The aim of this study was to show the correlation between athletes’ cardiac modifications and myocardial fibrosis with a native T1 mapping technique. A total of 41 healthy non-athletic control subjects and 46 athletes underwent CMR imaging. After the functional and morphological assessments, native T1 mapping was performed in all subjects using 3.0 T magnetic resonance imaging. Most of the CMR findings were significantly higher in athletes who had C5 years of sports activity when compared with non-athletic controls and athletes who had \5 years of sports activity. Significantly higher results were shown in native T1 values in athletes who had \5 years of sports activity, but there were no significant differences in the left ventricular end-diastolic volume, left ventricular end-diastolic mass, or interventricular septal wall thickness between non-athletic controls and athletes who had \5 years of sports activity. The native T1 mapping technique has the potential to discriminate myocardial fibrotic changes in athletes when compared to a normal myocardium. The T1 mapping method might be a feasible technique to evaluate athletes because it does not involve contrast, is non-invasive and allows for easy evaluation of myocardial remodeling.Öğe Assessment of urinary incontinence in the women in Eastern Turkey(International Urogynecology Journal, 2013) Altıntaş, Ramazan; Beytur, Ali; Oğuz, Fatih; Taşdemir, Cemal; Katı, Bülent; Çimen, Serhan; Çolak, Cemil; Güneş, AliIntroduction and hypothesis The aims of the present study were to determine the types of UI among women visiting the urology department, to identify the potential risk factors associated with each type of UI, and to identify healthcare-seeking behaviors of affected women in our region. Methods The data of 617 community-dwelling women, who were at least 18 years of age or older and who presented with a complaint of UI ongoing over a year, and those without UI, who were admitted for any other reason, from June 2010 to April 2012, were evaluated. Results Mean age was 51.29 years (range 18–110 years); median parity was 3.54 (range 0–11) and 88.2 % of the women were married. Mean BMI was 28.01 kg/m2 . Very few women (18.5 %) accepted UI as a disease and searched for medical help by themselves; however, the remaining women (81.5 %) were brought or directed for evaluation by someone else. Stress UI was reported by 43 women (10.5 %), urge UI and mixed UI were noted by 153 (37.5 %) and 212 (52 %) women respectively. Conclusions The most frequent type of UI was mixed UI in our region. Age, BMI, multiparity, and hypertension were identified to have a different importance for each type of UI, but diabetes mellitus, birth trauma, gynecological surgery, lumbar disc hernia (LDH), and multiple sclerosis (MS) were the other important related factors. However, a small number of patients accepted UI as a disease and searched for therapy This reveals that the public should be informed in detail about female UI in developing countries.Öğe Ateroskleroz un tahmini için bir yapay sinir ağı(Ankara Üniversitesi Tıp Fakültesi Mecmuası, 2005) Çolak, Cemil; Çolak, Mehmet Cengiz; Atıcı, Mehmet AliAmaç: Bu çalışmada, ateroskleroz’un tahmin edilebilmesi için bir yapay sinir ağı oluşturulması amaçlanmıştır. Gereç ve Yöntem: Haziran 2003 ile Kasım 2003 tarihleri arasında, kesikli ve sürekli değişkenlerden oluşan yirmi adet klinik parametre, radial arterde ateroskleroz saptanan on hasta ile radial arterde ateroskleroz saptanmayan on beş hastadan elde edilmiştir. Yapay sinir ağları, ateroskleroz verilerine uygulanmıştır. Bulgular: Geliştirilen yapay sinir ağının toplam ayrımsama oranı, eğitim ve test verisinde sırasıyla % 86.6 ve % 80 olarak bulunmuştur. Sonuç: Yapay sinir ağlarının ateroskleroz’un tahmin edilmesinde oldukça yararlı olacağı sonucuna varılabilir. Ancak örnek sayısının az olması göz önünde bulundurulduğunda, daha güvenilir sonuçlar elde edebilmek için örnek sayısının artırılması önerilebilir. Anahtar sözcükler: Ateroskleroz, Klinik parametreler, Yapay sinir ağları Aim: An artificial neural network was aimed to develop for the prediction of atherosclerosis. Material and Method: Between June 2003 and November 2003, twenty clinical parameters containing continuous and discrete variables were obtained ten patients for whom atherrosclerosis was determined in radial artery and fifteen patients for whom atherrosclerosis does not exist. Artificial neural network was applied to atherosclerosis data. Results: Accuracy values of artificial neural network on training and testing data were 86.6% and 80% respectively. Conclusion: The developed artificial neural network may be very useful for the prediction of atherosclerosis. However, in view of small sample size, it may be proposed to increase the sample size to obtain more reliable results. Key words: Artificial neural network, Atherosclerosis, Clinical parametersÖğe Ateroskleroz'un tahmini için bir yapay sinir ağı(2005) Çolak, M. Cengiz; Çolak, Cemil; Atıcı, M. AliAmaç; Bu çalışmada, ateroskleroz'un tahmin edilebilmesi için bir yapay sinir ağı oluşturulması amaçlanmıştır. Gereç ve Yöntem: Haziran 2003 ile Kasım 2003 tarihleri arasında, kesikli ve sürekli değişkenlerden oluşan yirmi adet klinik parametre, radial arterde ateroskleroz saptanan on hasta ile radial arterde ateroskleroz saptanmayan on beş hastadan elde edilmiştir. Yapay sinir ağları, ateroskleroz verilerine uygulanmıştır. Bulgular: Geliştirilen yapay sinir ağının toplam ayrımsama oranı, eğitim ve test verisinde sırasıyla % 86.6 ve % 80 olarak bulunmuştur. Sonuç: Yapay sinir ağlarının ateroskleroz'un tahmin edilmesinde oldukça yararlı olacağı sonucuna varılabilir. Ancak örnek sayısının az olması göz önünde bulundurulduğunda, daha güvenilir sonuçlar elde edebilmek için örnek sayısının artırılması önerilebilir.Öğe Aterosklerozun tahmini için bir yapay sinir ağı(Ankara Üniversitesi Tıp Fakültesi Mecmuası, 2005) Çolak, Cemil; Çolak, Mehmet Cengiz; Atıcı, M.AliAmaç: Bu çalışmada, ateroskleroz’un tahmin edilebilmesi için bir yapay sinir ağı oluşturulması amaçlanmıştır. Gereç ve Yöntem: Haziran 2003 ile Kasım 2003 tarihleri arasında, kesikli ve sürekli değişkenlerden oluşan yirmi adet klinik parametre, radial arterde ateroskleroz saptanan on hasta ile radial arterde ateroskleroz saptanmayan on beş hastadan elde edilmiştir. Yapay sinir ağları, ateroskleroz verilerine uygulanmıştır. Bulgular: Geliştirilen yapay sinir ağının toplam ayrımsama oranı, eğitim ve test verisinde sırasıyla % 86.6 ve % 80 olarak bulunmuştur. Sonuç: Yapay sinir ağlarının ateroskleroz’un tahmin edilmesinde oldukça yararlı olacağı sonucuna varılabilir. Ancak örnek sayısının az olması göz önünde bulundurulduğunda, daha güvenilir sonuçlar elde edebilmek için örnek sayısının artırılması önerilebilir. Anahtar sözcükler: Ateroskleroz, Klinik parametreler, Yapay sinir ağları Aim: An artificial neural network was aimed to develop for the prediction of atherosclerosis. Material and Method: Between June 2003 and November 2003, twenty clinical parameters containing continuous and discrete variables were obtained ten patients for whom atherrosclerosis was determined in radial artery and fifteen patients for whom atherrosclerosis does not exist. Artificial neural network was applied to atherosclerosis data. Results: Accuracy values of artificial neural network on training and testing data were 86.6% and 80% respectively. Conclusion: The developed artificial neural network may be very useful for the prediction of atherosclerosis. However, in view of small sample size, it may be proposed to increase the sample size to obtain more reliable results.Öğe Bernstein polynomial approach against to some frequently used growthcurve models on animal data(Pakistan journal of statistics, 2010) Gürcan, Mehmet; Çolak, Cemil; Orman, Mehmet N.Non-linear Logistic, Gompertz and Richards growth curve models were fitted to the data from Simmental x Southern Anatolian Red (SAR) crossbred cattles. Individual growth curves were fitted based on live weight measurements, and then general growth curves were obtained for all the models. In addition, Bernstein basis polynomials have played important roles in nonparametric curve estimation. Therefore, Bernstein polynomial approach was used to model the growth curve in the current data. We determined the accuracy of the models by using coefficient of determination 2 R , mean square error (MSE) and iteration number together. In summary, the most suitable model based on the accuracy criteria was Bernstein model. Among the well-known growth curves, Logistic, Richards and Gompertz were ordered respectively.
