CEMİL ÇOLAK - Academia.edu (original) (raw)

Papers by CEMİL ÇOLAK

Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun ta... more Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun tahmini ve etki eden risk faktörlerinin incelenmesi amaçlanmıştır. Radial arterde ateroskleroz saptanan 10 hastanın oluşturduğu grubun (Grup 1) verileri, radial arterde ateroskleroz saptanmayan 15 hastanın (Grup 2) verileriyle karşılaştırılmıştır. Hastaların yaş, cinsiyet, diabetes mellitus, hipertansiyon, sigara içme, obezite, aile öyküsü, kolesterol, trigliserit, yüksek dansiteli lipoprotein, düşük dansiteli lipoprotein, çok düşük dansiteli lipoprotein, apoprotein A, apoprotein B, lipoprotein A, C-reaktif protein, katalaz, glutat peroksidaz ve süperoksid dismutaz değişkenlerden oluşan on dokuz adet klinik parametre, Grup 1 ve 2’den elde edilmiştir. Risk faktörlerinin incelenmesinde gruplar istatistiksel olarak karşılaştırılmıştır. Ayrıca tek ve çok değişkenli lojistik regresyon analizi uygulanarak sonuçlar yorumlanmıştır. Sonuç olarak, geleneksel ve yeni risk faktörlerin ölçülebilen değe...

Medical Records

Aim: Data mining is the discovery process of beneficial information, not revealed from large-scal... more Aim: 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 ...

2019 International Artificial Intelligence and Data Processing Symposium (IDAP), 2019

In this study, it is aimed to develop a user-friendly open-source web-based software which enable... more In this study, it is aimed to develop a user-friendly open-source web-based software which enables the assignment of the subjects included in the scientific research to the groups with equal probability. An open source R package, Shiny, is used to develop the recommended web tool. In the developed software, one of the required equilibrium methods; random allocation rule, truncated binomial design, maximal procedure design, complete randomization methods; complete randomization design, blocking methods; permuted block randomization with random block constellation, the Hadamard randomization, adaptive methods; the big stick design, Efron's biased coin design, Wei's urn design, generalized biased coin design, Chen's biased coin design are included. A random allocation rule, one of the random assignment methods, is applied to a hypothetical data set where the sample size is 140 and the number of groups are two. As a result, in the first group, a random assignment was made in such a way that the number of samples are 70 and the number of samples in the second group are 70. According to the hypothetical data set findings, the developed easily assigns the subjects to the study groups by using random assignment methods. Therefore, it is stated that it easily solved a significant bias problem in scientific studies. In the following stages of the study, the scope of the software can be expanded with the addition of techniques comparing the results of random assignment methods.

Fırat Üniversitesi Sağlık Bilimleri Tıp Dergisi, 2019

Isgucune katilma durumunu etkileyen bagimsiz degiskenler; goc, cinsiyet, yas, hanehalki buyuklugu... more Isgucune katilma durumunu etkileyen bagimsiz degiskenler; goc, cinsiyet, yas, hanehalki buyuklugu, maas, egitim, calisma durumu, calistigi sektor, enflasyon ve isgucu endeksleri olarak belirlenmistir. Belirlenen degiskenlerin optimum olceklendirme ile bagimli degisken uzerindeki beklenen varyansi aciklama oranini gorerek, degiskenlerin kismi katkilarini ve istatistiksel anlamliliklarini incelemek amaclanmistir. Analizler, TUIK (Turkiye Istatistik Kurumu) Hanehalki Isgucu verilerinin 2016 yilina ait son alti aylik verileri uzerinden 2463 hane verisine kategorik regresyon (CATREG) uygulanmistir. Cozumleme, IBM SPSS Statistics 20 programinda yapilmistir. Veri yapisina uygun olceklendirme ile cozumleme yapildiginda, R^2 degeri model anlamli cikmasina ragmen yuksek seviyede cikmamistir. Optimum olceklendirme ile degiskenler tekrardan belli bir kisit dahilinde olceklendirildiginde, modelin anlamli ve R^2 degerinin belirgin sekilde arttigi tespit edilmistir. Bu kapsamda optimal olceklemeni...

Aim: The second-largest cause of cancer mortality for women is breast cancer. The main techniques... more Aim: The second-largest cause of cancer mortality for women is breast cancer. The main techniques for diagnosing breast cancer are mammography and tumor biopsy accompanied by histopathological studies. The mammograms are not detective of all subtypes of breast tumors, particularly those which arise and are more aggressive in young women or women with dense breast tissue. Circulating prognostic molecules and liquid biopsy approaches to detect breast cancer and the death risk are desperately essential. The purpose of this study is to develop a web-based tool for the use of the associative classification method that can classify breast cancer using the association rules method. Materials and Methods: In this study, an open-access dataset named “Breast Cancer Wisconsin (Diagnostic) Data Set” was used for the classification. To create this web-based application, the Shiny library is used, which allows the design of interactive web-based applications based on the R programming language. C...

Biomedical Research-tokyo, 2017

Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classificatio... more Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classification of this condition is of great importance in terms of clinical decision making. The purpose of the study is to design an intelligent system for the classification of postoperative pleural effusion between 4 and 30 days after surgery by medical knowledge discovery (MKD) methods. Materials and Methods: This study included 2309 individuals diagnosed with coronary artery disease for elective coronary artery bypass grafting (CABG) operation. The results of chest x-ray were used to diagnose PE. The subjects were allocated to two groups: PE group (n=81) and non-PE group (n=2228), consecutively. In the preprocessing step, outlier analysis, data transformation and feature selection processes were performed. In the data mining step, Naive Bayes, Bayesian network and Random Forest algorithms were utilized. Accuracy and area under receiver operating characteristics (ROC) curve (AUC) were calculated...

International Journal of Clinical Practice, 2021

COVID‐19 pandemic has created a serious psychological impact worldwide since it has been declared... more COVID‐19 pandemic has created a serious psychological impact worldwide since it has been declared. This study aims to investigate the level of psychological impacts of the COVID‐19 pandemic on the Turkish population and to determine related factors.

Purpose: COVID-19 pandemic has created a serious psychological impact worldwide since it has been... more Purpose: COVID-19 pandemic has created a serious psychological impact worldwide since it has been declared. This study aims to investigate the level of psychological impacts of COVID-19 pandemic on Turkish population and to determine related factors. Methods: The study was carried out by using an online questionnaire using the virtual snowball sampling method. The sociodemographic data were collected on the following subjects: Participants' experience on any signs of infection within the last month, the history of COVID-19 contact-treatment-quarantine, level of compliance with precautionary measures, the

Computer methods and programs in biomedicine, 2016

Medical data mining (also called knowledge discovery process in medicine) processes for extractin... more Medical data mining (also called knowledge discovery process in medicine) processes for extracting patterns from large datasets. In the current study, we intend to assess different medical data mining approaches to predict ischemic stroke. The collected dataset from Turgut Ozal Medical Centre, Inonu University, Malatya, Turkey, comprised the medical records of 80 patients and 112 healthy individuals with 17 predictors and a target variable. As data mining approaches, support vector machine (SVM), stochastic gradient boosting (SGB) and penalized logistic regression (PLR) were employed. 10-fold cross validation resampling method was utilized, and model performance evaluation metrics were accuracy, area under ROC curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The grid search method was used for optimizing tuning parameters of the models. The accuracy values with 95% CI were 0.9789 (0.9470-0.9942) for SVM, 0.9737 (0.9397-0.9914) for SGB a...

Journal of Inonu University Medical Faculty, 2012

The researchers need to be aware of the design, methodology, analysis and interpretation of the s... more The researchers need to be aware of the design, methodology, analysis and interpretation of the studies to assess effectively the results of animal experiments. This can be achieved with the published research standards or guidelines. ARRIVE guidelines (Animals in Research: Reporting In Vivo Experiments) have been published to improve the quality and transparency of studies of animal experiments in the British Journal of Pharmacology in 2010. This study was carried out to review the studies related to ARRIVE guidelines. Key words: ARRIVE Guidelines; Animal Experiments; Checklist.

uludagtipdergisi.org

Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun ta... more Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun tahmini ve etki eden risk faktörlerinin incelenmesi amaçlanmıştır. Radial arterde ateroskleroz saptanan 10 hastanın oluşturduğu grubun (Grup 1) verileri, radial arterde ateroskleroz saptanmayan 15 hastanın (Grup 2) verileriyle karşılaştırılmıştır. Hastaların yaş, cinsiyet, diabetes mellitus, hipertansiyon, sigara içme, obezite, aile öyküsü, kolesterol, trigliserit, yüksek dansiteli lipoprotein, düşük dansiteli lipoprotein, çok düşük dansiteli lipoprotein, apoprotein A, apoprotein B, lipoprotein A, C-reaktif protein, katalaz, glutat peroksidaz ve süperoksid dismutaz değişkenlerden oluşan on dokuz adet klinik parametre, Grup 1 ve 2'den elde edilmiştir. Risk faktörlerinin incelenmesinde gruplar istatistiksel olarak karşılaştırılmıştır. Ayrıca tek ve çok değişkenli lojistik regresyon analizi uygulanarak sonuçlar yorumlanmıştır. Sonuç olarak, geleneksel ve yeni risk faktörlerin ölçülebilen değer ve oranları, koroner arter hastalarına oranla radial arterde ateroskleroz saptanan koroner arter hastalarında daha yüksektir. Risk faktörlerinin incelenmesinde çok değişkenli istatistik yöntemlerinin daha büyük bir örnekte uygulanması daha yararlı olacaktır. Anahtar Kelimeler: Ateroskleroz. Lojistik regresyon analizi. Risk faktörleri.

La radiologia medica, 2016

The aim of this study was to examine the correlation between ventricular function and the extrace... more The aim of this study was to examine the correlation between ventricular function and the extracellular volume fraction (ECV) in patients with non-ischemic dilated cardiomyopathy (NIDCM) using 3.0 T magnetic resonance imaging (MRI). We also hypothesized that native T1 and ECV values would be increased in patients with NIDCM, independent of the left ventricular ejection fraction (LVEF). The findings of our study could lead to further studies of the follow-up protocols. In total, 53 consecutive dilated cardiomyopathy patients who had undergone cardiac MRI were functionally evaluated and underwent tissue characterization. The mean native T1 value was 1235 ± 10 ms, and the mean ECV value was 35.4 ± 2.7% in the myocardia. The LVEF values ranged from 29 to 44%. No significant correlations were observed between functional analysis measurements and native T1 or ECV values. Our results showed that myocardial fibrosis is unrelated to cardiac functional findings in NIDCM patients. Therefore, we propose that these patients should be evaluated using MRI and tissue characterization techniques, in addition to cardiac functional analysis.

Knee Surgery, Sports Traumatology, Arthroscopy, 2015

In the early OA subgroups, significantly better clinical results were achieved in the patients tr... more In the early OA subgroups, significantly better clinical results were achieved in the patients treated with three PRP injections, but there was no significant difference in the clinical results of patients with advanced OA among the treatment groups. Conclusion The clinical results of this study suggest IA PRP and HA treatment for all stages of knee OA. For patients with early OA, multiple (3) PRP injections are useful in achieving better clinical results. For patients with advanced OA, multiple injections do not significantly improve the results of patients in any group. Level of evidence I.

The International Journal of Cardiovascular Imaging, 2016

Intensive physical exercise leads to increases in left ventricular muscle mass and wall thickness... more 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 ≥5 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.

Middle Black Sea Journal of Health Science, 2021

Objective: In recent years, ensemble learning methods have gained widespread use for early diagno... more Objective: In recent years, ensemble learning methods have gained widespread use for early diagnosis of cancer diseases. In this study, it is aimed to establish a high-performance ensemble learning model for early diagnosis and classification of renal cell carcinomas. Methods: In the study, hemogram and laboratory data of 140 patients with renal cell carcinoma and 140 patients without renal cell carcinoma were included in the study. The data set includes 27 predictors and 1 dependent variable. The data were obtained retrospectively. In the study, classification performances of machine learning methods and ensemble learning methods were compared. In the study, classification performances of boosting, bagging, voting and stacking ensemble learning methods as well as IB1, IBk, Kstar, LWL, REPTree, Random Forest and SMO classifiers were compared. Results: REPTree classifier provided the highest performance among machine learning methods (Accuracy = 0.867). Among the ensemble learning methods, the Stacking ensemble learning method provided the highest performance in Model 6 (Accuracy = 0.906). Stacking ensemble learning methods performed higher than boosting, voting, bagging ensemble methods and machine learning methods. Conclusion: Stacking ensemble learning methods provide successful results in the early diagnosis of renal cell carcinomas. Stacking ensemble learning methods can be used as an alternative to existing methods for diagnosing renal cell carcinoma. In order to further increase the classification performance of the stacking ensemble learning method, it is recommended to choose a meta classifier suitable for the data set and variable types.

Journal of Clinical and Experimental Investigations, 2013

Çocuklarda ve erişkinlerdeki refraksiyon kusuru ölçümünde, Plusoptix S08 ile standart bir oto ref... more Çocuklarda ve erişkinlerdeki refraksiyon kusuru ölçümünde, Plusoptix S08 ile standart bir oto refraktometre (Topcon RM 8000B) ölçümlerinin karşılaştırılması. Yöntemler: Yaş ortalaması 8.06 ± 2.89 yıl olan 110 çocuğun 220 gözü Plusoptix S08 ile sikloplejisiz olarak, Topcon RM-8000B otorefraktometresiyle sikloplejili olarak ölçüldü. Elde edilen değerler karşılaştırıldı. Ayrıca, yaş ortalaması 33,3 ± 13,4 olan 127 yetişkinin 254 gözü, Plusoptix S08 ve Topcon RM 8000B otorefraktometre ile sikloplejisiz olarak ölçülerek, bu ölçümlerin karşılaştırması yapıldı. Tüm ölçümler üç kez tekrarlandı. Ortalama sferik, silindirik, sferik ekivalan ve silindirik aks değerleri istatistiksel olarak karşılaştırıldı.

Ankara Üniversitesi Veteriner Fakültesi Dergisi, 2006

1 genotiplerine ilişkin beden ölçüleri için doğrusal ve doğrusal olmayan lojistik büyüme modeller... more 1 genotiplerine ilişkin beden ölçüleri için doğrusal ve doğrusal olmayan lojistik büyüme modelleri oluşturulmuştur. Doğrusal ve lojistik büyüme modellerine ait artıklarda ortaya çıkabilecek özilişki sorunu incelenmiştir. Modellerinin uyum iyiliği, hata kareler ortalaması ve belirleme katsayısı değerleri kullanılarak yapılmıştır. Sonuç olarak, beden ölçülerinin tanımlanmasında doğrusal olmayan lojistik modelinin doğrusal modelden daha başarılı olduğu uyum iyiliği ölçütleri ile tespit edilmiştir. Anahtar sözcükler: Beden ölçüleri, büyüme modeli, sığır, Güney Anadolu Kırmızısı, Simental. Simple linear and logistic growth model for the body measurements of Simmental x Southern Anatolian Red crossbred cattle Summary: In this study, linear and nonlinear logistic growth models were obtained for the body measurements of Simmental x Southern Anatolian Red crossbred cattle B 1 and F 1 xB 1 genotypes. It was studied the autocorrelation of the residuals from the linear and logistic growth curve models. Goodness of fit of the models was determined by mean square error (MSE) and determination coefficient values. As a result, logistic growth curve model was more successful than linear model in the description of body measurements according to goodness of fit criterions.

Turkiye Klinikleri Journal of Biostatistics

The main purpose of this research is to develop a novel user-friendly web tool based on machine l... more The main purpose of this research is to develop a novel user-friendly web tool based on machine learning approaches, which applies a variety of techniques to address the class imbalance problem. Material and Methods: Shiny, an opensource R package, was used to develop the proposed web tool. The interactive tool can handle the class imbalance problem for binary classification dataset(s) by implementing sampling-based methods. As a clinical application, the dataset retrospectively obtained from the database of the

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

In this study, it was aimed to develop a new user-friendly web-based software that would easily t... more In this study, it was aimed to develop a new user-friendly web-based software that would easily test single-variable univariate and multivariate normal distribution suitability and enable users to get more accurate results in their studies.Shiny, an open source R package, was used to develop the proposed web software. In the developed software, Shapiro-Wilk and Anderson-Darling tests were used for the uniformity of univariate distribution, and Mardia's skewness-kurtosis, Henze-Zircon and Doornik-Hansen tests were used for multivariate normal distribution. Outputs for conformity to normal distribution were supported by using graphical methods. In practice, for the data set where each variable consisting of two variables derived by simulation has a standard normal distribution and the variables contain 1000 observations, the normal distribution conformity analysis has been performed. In the derived data set, each variable is normally distributed according to the Anderson-Darling and Shapiro-Wilk tests.In addition, the derived data set showed normal distribution with three variables according to Mardia's skewness-kurtosis and Henze-Zirkler tests. However, according to the Doornik-Hansen test, the triple does not show normal distribution.The developed software is a new user-friendly web-based software that can easily perform univariate and multivariate normal distribution conformity analysis and enable users to get more accurate results in their work. In further studies, Type I and Type II error types are planned to be included in the software in order to determine the best method.

Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun ta... more Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun tahmini ve etki eden risk faktörlerinin incelenmesi amaçlanmıştır. Radial arterde ateroskleroz saptanan 10 hastanın oluşturduğu grubun (Grup 1) verileri, radial arterde ateroskleroz saptanmayan 15 hastanın (Grup 2) verileriyle karşılaştırılmıştır. Hastaların yaş, cinsiyet, diabetes mellitus, hipertansiyon, sigara içme, obezite, aile öyküsü, kolesterol, trigliserit, yüksek dansiteli lipoprotein, düşük dansiteli lipoprotein, çok düşük dansiteli lipoprotein, apoprotein A, apoprotein B, lipoprotein A, C-reaktif protein, katalaz, glutat peroksidaz ve süperoksid dismutaz değişkenlerden oluşan on dokuz adet klinik parametre, Grup 1 ve 2’den elde edilmiştir. Risk faktörlerinin incelenmesinde gruplar istatistiksel olarak karşılaştırılmıştır. Ayrıca tek ve çok değişkenli lojistik regresyon analizi uygulanarak sonuçlar yorumlanmıştır. Sonuç olarak, geleneksel ve yeni risk faktörlerin ölçülebilen değe...

Medical Records

Aim: Data mining is the discovery process of beneficial information, not revealed from large-scal... more Aim: 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 ...

2019 International Artificial Intelligence and Data Processing Symposium (IDAP), 2019

In this study, it is aimed to develop a user-friendly open-source web-based software which enable... more In this study, it is aimed to develop a user-friendly open-source web-based software which enables the assignment of the subjects included in the scientific research to the groups with equal probability. An open source R package, Shiny, is used to develop the recommended web tool. In the developed software, one of the required equilibrium methods; random allocation rule, truncated binomial design, maximal procedure design, complete randomization methods; complete randomization design, blocking methods; permuted block randomization with random block constellation, the Hadamard randomization, adaptive methods; the big stick design, Efron's biased coin design, Wei's urn design, generalized biased coin design, Chen's biased coin design are included. A random allocation rule, one of the random assignment methods, is applied to a hypothetical data set where the sample size is 140 and the number of groups are two. As a result, in the first group, a random assignment was made in such a way that the number of samples are 70 and the number of samples in the second group are 70. According to the hypothetical data set findings, the developed easily assigns the subjects to the study groups by using random assignment methods. Therefore, it is stated that it easily solved a significant bias problem in scientific studies. In the following stages of the study, the scope of the software can be expanded with the addition of techniques comparing the results of random assignment methods.

Fırat Üniversitesi Sağlık Bilimleri Tıp Dergisi, 2019

Isgucune katilma durumunu etkileyen bagimsiz degiskenler; goc, cinsiyet, yas, hanehalki buyuklugu... more Isgucune katilma durumunu etkileyen bagimsiz degiskenler; goc, cinsiyet, yas, hanehalki buyuklugu, maas, egitim, calisma durumu, calistigi sektor, enflasyon ve isgucu endeksleri olarak belirlenmistir. Belirlenen degiskenlerin optimum olceklendirme ile bagimli degisken uzerindeki beklenen varyansi aciklama oranini gorerek, degiskenlerin kismi katkilarini ve istatistiksel anlamliliklarini incelemek amaclanmistir. Analizler, TUIK (Turkiye Istatistik Kurumu) Hanehalki Isgucu verilerinin 2016 yilina ait son alti aylik verileri uzerinden 2463 hane verisine kategorik regresyon (CATREG) uygulanmistir. Cozumleme, IBM SPSS Statistics 20 programinda yapilmistir. Veri yapisina uygun olceklendirme ile cozumleme yapildiginda, R^2 degeri model anlamli cikmasina ragmen yuksek seviyede cikmamistir. Optimum olceklendirme ile degiskenler tekrardan belli bir kisit dahilinde olceklendirildiginde, modelin anlamli ve R^2 degerinin belirgin sekilde arttigi tespit edilmistir. Bu kapsamda optimal olceklemeni...

Aim: The second-largest cause of cancer mortality for women is breast cancer. The main techniques... more Aim: The second-largest cause of cancer mortality for women is breast cancer. The main techniques for diagnosing breast cancer are mammography and tumor biopsy accompanied by histopathological studies. The mammograms are not detective of all subtypes of breast tumors, particularly those which arise and are more aggressive in young women or women with dense breast tissue. Circulating prognostic molecules and liquid biopsy approaches to detect breast cancer and the death risk are desperately essential. The purpose of this study is to develop a web-based tool for the use of the associative classification method that can classify breast cancer using the association rules method. Materials and Methods: In this study, an open-access dataset named “Breast Cancer Wisconsin (Diagnostic) Data Set” was used for the classification. To create this web-based application, the Shiny library is used, which allows the design of interactive web-based applications based on the R programming language. C...

Biomedical Research-tokyo, 2017

Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classificatio... more Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classification of this condition is of great importance in terms of clinical decision making. The purpose of the study is to design an intelligent system for the classification of postoperative pleural effusion between 4 and 30 days after surgery by medical knowledge discovery (MKD) methods. Materials and Methods: This study included 2309 individuals diagnosed with coronary artery disease for elective coronary artery bypass grafting (CABG) operation. The results of chest x-ray were used to diagnose PE. The subjects were allocated to two groups: PE group (n=81) and non-PE group (n=2228), consecutively. In the preprocessing step, outlier analysis, data transformation and feature selection processes were performed. In the data mining step, Naive Bayes, Bayesian network and Random Forest algorithms were utilized. Accuracy and area under receiver operating characteristics (ROC) curve (AUC) were calculated...

International Journal of Clinical Practice, 2021

COVID‐19 pandemic has created a serious psychological impact worldwide since it has been declared... more COVID‐19 pandemic has created a serious psychological impact worldwide since it has been declared. This study aims to investigate the level of psychological impacts of the COVID‐19 pandemic on the Turkish population and to determine related factors.

Purpose: COVID-19 pandemic has created a serious psychological impact worldwide since it has been... more Purpose: COVID-19 pandemic has created a serious psychological impact worldwide since it has been declared. This study aims to investigate the level of psychological impacts of COVID-19 pandemic on Turkish population and to determine related factors. Methods: The study was carried out by using an online questionnaire using the virtual snowball sampling method. The sociodemographic data were collected on the following subjects: Participants' experience on any signs of infection within the last month, the history of COVID-19 contact-treatment-quarantine, level of compliance with precautionary measures, the

Computer methods and programs in biomedicine, 2016

Medical data mining (also called knowledge discovery process in medicine) processes for extractin... more Medical data mining (also called knowledge discovery process in medicine) processes for extracting patterns from large datasets. In the current study, we intend to assess different medical data mining approaches to predict ischemic stroke. The collected dataset from Turgut Ozal Medical Centre, Inonu University, Malatya, Turkey, comprised the medical records of 80 patients and 112 healthy individuals with 17 predictors and a target variable. As data mining approaches, support vector machine (SVM), stochastic gradient boosting (SGB) and penalized logistic regression (PLR) were employed. 10-fold cross validation resampling method was utilized, and model performance evaluation metrics were accuracy, area under ROC curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The grid search method was used for optimizing tuning parameters of the models. The accuracy values with 95% CI were 0.9789 (0.9470-0.9942) for SVM, 0.9737 (0.9397-0.9914) for SGB a...

Journal of Inonu University Medical Faculty, 2012

The researchers need to be aware of the design, methodology, analysis and interpretation of the s... more The researchers need to be aware of the design, methodology, analysis and interpretation of the studies to assess effectively the results of animal experiments. This can be achieved with the published research standards or guidelines. ARRIVE guidelines (Animals in Research: Reporting In Vivo Experiments) have been published to improve the quality and transparency of studies of animal experiments in the British Journal of Pharmacology in 2010. This study was carried out to review the studies related to ARRIVE guidelines. Key words: ARRIVE Guidelines; Animal Experiments; Checklist.

uludagtipdergisi.org

Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun ta... more Bu çalışmada, koroner arter hastalarında greft olarak kullanılan radial arterde aterosklerozun tahmini ve etki eden risk faktörlerinin incelenmesi amaçlanmıştır. Radial arterde ateroskleroz saptanan 10 hastanın oluşturduğu grubun (Grup 1) verileri, radial arterde ateroskleroz saptanmayan 15 hastanın (Grup 2) verileriyle karşılaştırılmıştır. Hastaların yaş, cinsiyet, diabetes mellitus, hipertansiyon, sigara içme, obezite, aile öyküsü, kolesterol, trigliserit, yüksek dansiteli lipoprotein, düşük dansiteli lipoprotein, çok düşük dansiteli lipoprotein, apoprotein A, apoprotein B, lipoprotein A, C-reaktif protein, katalaz, glutat peroksidaz ve süperoksid dismutaz değişkenlerden oluşan on dokuz adet klinik parametre, Grup 1 ve 2'den elde edilmiştir. Risk faktörlerinin incelenmesinde gruplar istatistiksel olarak karşılaştırılmıştır. Ayrıca tek ve çok değişkenli lojistik regresyon analizi uygulanarak sonuçlar yorumlanmıştır. Sonuç olarak, geleneksel ve yeni risk faktörlerin ölçülebilen değer ve oranları, koroner arter hastalarına oranla radial arterde ateroskleroz saptanan koroner arter hastalarında daha yüksektir. Risk faktörlerinin incelenmesinde çok değişkenli istatistik yöntemlerinin daha büyük bir örnekte uygulanması daha yararlı olacaktır. Anahtar Kelimeler: Ateroskleroz. Lojistik regresyon analizi. Risk faktörleri.

La radiologia medica, 2016

The aim of this study was to examine the correlation between ventricular function and the extrace... more The aim of this study was to examine the correlation between ventricular function and the extracellular volume fraction (ECV) in patients with non-ischemic dilated cardiomyopathy (NIDCM) using 3.0 T magnetic resonance imaging (MRI). We also hypothesized that native T1 and ECV values would be increased in patients with NIDCM, independent of the left ventricular ejection fraction (LVEF). The findings of our study could lead to further studies of the follow-up protocols. In total, 53 consecutive dilated cardiomyopathy patients who had undergone cardiac MRI were functionally evaluated and underwent tissue characterization. The mean native T1 value was 1235 ± 10 ms, and the mean ECV value was 35.4 ± 2.7% in the myocardia. The LVEF values ranged from 29 to 44%. No significant correlations were observed between functional analysis measurements and native T1 or ECV values. Our results showed that myocardial fibrosis is unrelated to cardiac functional findings in NIDCM patients. Therefore, we propose that these patients should be evaluated using MRI and tissue characterization techniques, in addition to cardiac functional analysis.

Knee Surgery, Sports Traumatology, Arthroscopy, 2015

In the early OA subgroups, significantly better clinical results were achieved in the patients tr... more In the early OA subgroups, significantly better clinical results were achieved in the patients treated with three PRP injections, but there was no significant difference in the clinical results of patients with advanced OA among the treatment groups. Conclusion The clinical results of this study suggest IA PRP and HA treatment for all stages of knee OA. For patients with early OA, multiple (3) PRP injections are useful in achieving better clinical results. For patients with advanced OA, multiple injections do not significantly improve the results of patients in any group. Level of evidence I.

The International Journal of Cardiovascular Imaging, 2016

Intensive physical exercise leads to increases in left ventricular muscle mass and wall thickness... more 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 ≥5 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.

Middle Black Sea Journal of Health Science, 2021

Objective: In recent years, ensemble learning methods have gained widespread use for early diagno... more Objective: In recent years, ensemble learning methods have gained widespread use for early diagnosis of cancer diseases. In this study, it is aimed to establish a high-performance ensemble learning model for early diagnosis and classification of renal cell carcinomas. Methods: In the study, hemogram and laboratory data of 140 patients with renal cell carcinoma and 140 patients without renal cell carcinoma were included in the study. The data set includes 27 predictors and 1 dependent variable. The data were obtained retrospectively. In the study, classification performances of machine learning methods and ensemble learning methods were compared. In the study, classification performances of boosting, bagging, voting and stacking ensemble learning methods as well as IB1, IBk, Kstar, LWL, REPTree, Random Forest and SMO classifiers were compared. Results: REPTree classifier provided the highest performance among machine learning methods (Accuracy = 0.867). Among the ensemble learning methods, the Stacking ensemble learning method provided the highest performance in Model 6 (Accuracy = 0.906). Stacking ensemble learning methods performed higher than boosting, voting, bagging ensemble methods and machine learning methods. Conclusion: Stacking ensemble learning methods provide successful results in the early diagnosis of renal cell carcinomas. Stacking ensemble learning methods can be used as an alternative to existing methods for diagnosing renal cell carcinoma. In order to further increase the classification performance of the stacking ensemble learning method, it is recommended to choose a meta classifier suitable for the data set and variable types.

Journal of Clinical and Experimental Investigations, 2013

Çocuklarda ve erişkinlerdeki refraksiyon kusuru ölçümünde, Plusoptix S08 ile standart bir oto ref... more Çocuklarda ve erişkinlerdeki refraksiyon kusuru ölçümünde, Plusoptix S08 ile standart bir oto refraktometre (Topcon RM 8000B) ölçümlerinin karşılaştırılması. Yöntemler: Yaş ortalaması 8.06 ± 2.89 yıl olan 110 çocuğun 220 gözü Plusoptix S08 ile sikloplejisiz olarak, Topcon RM-8000B otorefraktometresiyle sikloplejili olarak ölçüldü. Elde edilen değerler karşılaştırıldı. Ayrıca, yaş ortalaması 33,3 ± 13,4 olan 127 yetişkinin 254 gözü, Plusoptix S08 ve Topcon RM 8000B otorefraktometre ile sikloplejisiz olarak ölçülerek, bu ölçümlerin karşılaştırması yapıldı. Tüm ölçümler üç kez tekrarlandı. Ortalama sferik, silindirik, sferik ekivalan ve silindirik aks değerleri istatistiksel olarak karşılaştırıldı.

Ankara Üniversitesi Veteriner Fakültesi Dergisi, 2006

1 genotiplerine ilişkin beden ölçüleri için doğrusal ve doğrusal olmayan lojistik büyüme modeller... more 1 genotiplerine ilişkin beden ölçüleri için doğrusal ve doğrusal olmayan lojistik büyüme modelleri oluşturulmuştur. Doğrusal ve lojistik büyüme modellerine ait artıklarda ortaya çıkabilecek özilişki sorunu incelenmiştir. Modellerinin uyum iyiliği, hata kareler ortalaması ve belirleme katsayısı değerleri kullanılarak yapılmıştır. Sonuç olarak, beden ölçülerinin tanımlanmasında doğrusal olmayan lojistik modelinin doğrusal modelden daha başarılı olduğu uyum iyiliği ölçütleri ile tespit edilmiştir. Anahtar sözcükler: Beden ölçüleri, büyüme modeli, sığır, Güney Anadolu Kırmızısı, Simental. Simple linear and logistic growth model for the body measurements of Simmental x Southern Anatolian Red crossbred cattle Summary: In this study, linear and nonlinear logistic growth models were obtained for the body measurements of Simmental x Southern Anatolian Red crossbred cattle B 1 and F 1 xB 1 genotypes. It was studied the autocorrelation of the residuals from the linear and logistic growth curve models. Goodness of fit of the models was determined by mean square error (MSE) and determination coefficient values. As a result, logistic growth curve model was more successful than linear model in the description of body measurements according to goodness of fit criterions.

Turkiye Klinikleri Journal of Biostatistics

The main purpose of this research is to develop a novel user-friendly web tool based on machine l... more The main purpose of this research is to develop a novel user-friendly web tool based on machine learning approaches, which applies a variety of techniques to address the class imbalance problem. Material and Methods: Shiny, an opensource R package, was used to develop the proposed web tool. The interactive tool can handle the class imbalance problem for binary classification dataset(s) by implementing sampling-based methods. As a clinical application, the dataset retrospectively obtained from the database of the

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

In this study, it was aimed to develop a new user-friendly web-based software that would easily t... more In this study, it was aimed to develop a new user-friendly web-based software that would easily test single-variable univariate and multivariate normal distribution suitability and enable users to get more accurate results in their studies.Shiny, an open source R package, was used to develop the proposed web software. In the developed software, Shapiro-Wilk and Anderson-Darling tests were used for the uniformity of univariate distribution, and Mardia's skewness-kurtosis, Henze-Zircon and Doornik-Hansen tests were used for multivariate normal distribution. Outputs for conformity to normal distribution were supported by using graphical methods. In practice, for the data set where each variable consisting of two variables derived by simulation has a standard normal distribution and the variables contain 1000 observations, the normal distribution conformity analysis has been performed. In the derived data set, each variable is normally distributed according to the Anderson-Darling and Shapiro-Wilk tests.In addition, the derived data set showed normal distribution with three variables according to Mardia's skewness-kurtosis and Henze-Zirkler tests. However, according to the Doornik-Hansen test, the triple does not show normal distribution.The developed software is a new user-friendly web-based software that can easily perform univariate and multivariate normal distribution conformity analysis and enable users to get more accurate results in their work. In further studies, Type I and Type II error types are planned to be included in the software in order to determine the best method.