ZEYNEP TUNÇ - Academia.edu (original) (raw)
Papers by ZEYNEP TUNÇ
2019 International Artificial Intelligence and Data Processing Symposium (IDAP), 2019
In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal... more In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal distribution of the new data set obtained by applying various mathematical transformations to data sets that do not meet the normal distribution from parametric hypothesis testing conditions. The web based software is developed by Shiny web framework, which is an open source R package. In the web-based software, arcsinh (x), Box-Cox, Exponential, Lambert W (h type), Lambert W (s type), Logarithmic, Square root, Yeo-Johnson data transformation methods are used. The software also allows us to decide on the best conversion for the data set to be transformed by calculating the Pearson P test statistic, which chooses on the best method in the methods used. This is done by selecting the conversion with the smallest Pearson P statistic. In order to evaluate the outputs of the software, a data set with three variables was derived with the Cauchy, gamma, Weibull distributions respectively and 500 samples were used for each distribution. The developed software is novel user-friendly web-based software that enables researchers to get more accurate results in their work and to obtain data transformation methods that provide parametric test assumptions known as more powerful tests.
The Journal of Cognitive Systems, Dec 31, 2020
This study aims to predict mortality status by heart failure and to determine the related factors... more This study aims to predict mortality status by heart failure and to determine the related factors by applying the relational classification method, one of the data mining methods, on the openaccess heart failure data set. Materials and Methods: In this study, the associative classification model has been applied to the open-access data set named "Heart Failure Prediction". The performance of the model was evaluated by accuracy, balanced accuracy, sensitivity, selectivity, positive predictive value, negative predictive value, and F1-score.
Objective: In this study, it is aimed to classify type 2 Diabetes Mellitus (DM), compare the esti... more Objective: In this study, it is aimed to classify type 2 Diabetes Mellitus (DM), compare the estimates of the Artificial Neural Network models and determine the factors related to the disease by applying Multilayer Perceptron (MLP) and Radial Based Function (RBF) methods on the open-access dataset. Material and Methods: In this study, the data set named “Pima Indians Diabetes Database” was obtained from https://www.kaggle.com/uciml/pima-indians-diabetes-database. The dataset contains 768 records with 268 (34.9%) type 2 diabetes patients and 500 (65.1%) people without diabetes, which have 9 variables (8 inputs and 1 outcome). MLP and RBF methods, which are artificial neural network models, were used to classify type 2 DM. Factors associated with type 2 DM were estimated by using artificial neural network models. Results: The performance values obtained with MLP from the applied models were accuracy 78.1%, specificity 81.2%, AUC 0.848, sensitivity 71%, positive predictive value 61.7%,...
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...
Aim: In this study, it is aimed to classify breast cancer and identify related factors by applyin... more Aim: In this study, it is aimed to classify breast cancer and identify related factors by applying deep learning method on open access to breast cancer dataset. Materials and Methods: In this study, 11 variables related to open access to breast cancer dataset of 569 patients shared by the University of Wisconsin were used. The deep learning model for classifying breast cancer was established by a 10-fold cross-validation method. The performance of the model was evaluated with accuracy, sensitivity, specificity, positive/negative predictive values, F-score, and area under the curve (AUC). Factors associated with breast cancer were estimated from the deep learning model. Results: Accuracy, specificity, AUC, sensitivity, positive predictive value, negative predictive value, and F-score values obtained from the model were 94.91%, 91.47%, 0.988, 96.90%, 95.42%, 95.14%, and 96.03%, respectively. In this study, when the effects of the variables in the dataset on breast cancer were evaluate...
Middle Black Sea Journal of Health Science, 2020
Journal of Traditional Medical Complementary Therapies, 2020
Yoğun bakım (YB) ve palyatif bakım (PB) üniteleri yaşam sonu bakımın uygulandığı kliniklerdir. PB... more Yoğun bakım (YB) ve palyatif bakım (PB) üniteleri yaşam sonu bakımın uygulandığı kliniklerdir. PB hizmetlerinin optimal düzeyde verilebilmesi için bu ünitelerde çalışanların PB hakkında yeterli düzeyde bilgi sahibi olması gerekmektedir. Bu çalışmanın amacı, YB ve PB ünitelerinde çalışan doktor ve hemşirelerin PB'ye ilişkin bilgi ve görüşlerinin belirlenmesi ve karşılaştırılmasıdır. Gereç ve Yöntemler: Çalışma; Malatya Eğitim ve Araştırma Hastanesi Reanimasyon YB, Dahiliye YB ve PB ünitelerinde çalışan hekim ve hemşireler ile yüz yüze görüşme yöntemi ile yapılmıştır. Çalışmada veriler, sosyodemografik özellikler formu ve literatür bilgileri doğrultusunda hazırlanan, çalışanların PB'ye yönelik mevcut bilgi ve görüşlerini belirleyici anket formu kullanılarak elde edilmiştir. Bulgular: Çalışmaya katılanların (68 hemşire, 12 doktor) yaş ortalaması 34 olup, çoğunluğunu lisans mezunu kadınlar oluşturmaktaydı. Katılımcıların %80'i eğitimleri sırasında PB eğitimi almadıklarını ve %76,3'ü yapılacak eğitim programlarına ihtiyaç duyduklarını belirtti. YB çalışanlarının %37,5'i, PB çalışanlarının %20'si hospis tanımını bilmediklerini ifade etti. PB çalışanlarının çoğu (%85,1) tedavisi biten hastaların taburculuğunda zorlandıklarını ve %85,5'i PB'de tükenmişlik yaşadıklarını belirtti. YB hemşirelerinin %63,8'i "YB"de PB hizmeti verilmelidir, ifadesine katılmadıklarını ve bu konu hakkında bilgi sahibi olmadıklarını belirtti. Çalışanların tamamına yakını, PB temel eğitiminin üniversite eğitim programlarında zorunlu olması gerektiğini belirtti. Sonuç: YB ve PB ünitesinde çalışan sağlık personelinin "Palyatif bakım ve hospis" kavramları konusunda yeterli bilgiye sahip olmadıkları, bilgi düzeylerinde farklılıklar olduğu ve bu konuda yapılacak eğitim programlarına ihtiyaç duydukları belirlenmiştir. Bu durumun temel lisans eğitimindeki eksikliklerden kaynaklandığı, eğitim müfredatında zorunlu PB eğitim dersinin yer alması ve sertifikalı eğitim programlarının yaygınlaşması gerektiği düşünülmektedir. Anah tar Ke li me ler: Palyatif bakım; yoğun bakım; sağlık personeli; bilgi ABS TRACT Objective: Intensive care (ICU) and palliative care (PD) units are clinics where end-of-life care is applied. In order for PB services to be provided at an optimal level, employees working in these units should have sufficient knowledge about PB. The aim of this study is to determine and compare the knowledge and opinions of doctors and nurses working in the ICU and PD units about palliative care. Material and Methods: Study; Malatya Training and Research Hospital Reanimation YB, Internal Medicine YB and PB were conducted by face to face interviews with physicians and nurses working in the units. In the study, the data were obtained by using the questionnaire form, which was prepared in line with the socio-demographic characteristics form and the literature information, and which determines the current knowledge and opinions of the employees about PD. Results: The average age of the participants (68 nurses, 12 doctors) was 34, most of whom were undergraduate graduates. 80% of the participants stated that they did not receive PD training during their training and 76.3% of them stated that they needed training programs to be carried out. 37.5% of YB employees and 20% of PD employees stated that they do not know the definition of hospis. Most of the PD staff (85.1%) stated that the patients who had completed their treatment had difficulty in discharge and 85.5% of them experienced burnout in PD. 63.8% of the YB nurses stated that they disagree with the statement "PB service should be provided in YB" and they do not have any information about this subject. Almost all of the employees stated that PB basic education should be compulsory in university education programs. Conclusion: It was determined that the health personnel working in the YB and PD unit do not have sufficient information about the concepts of "Palliative care and hospice", there are differences in their knowledge levels and they need training programs to be carried out in this regard. It is thought that this situation is due to the deficiencies in basic undergraduate education, compulsory PB education courses should be included in the education curriculum and certified education programs should become widespread.
Turkiye Klinikleri Journal of Biostatistics, 2019
In a research, it is not desirable that the dataset to be used contains missing value (s) and res... more In a research, it is not desirable that the dataset to be used contains missing value (s) and researchers try to cope with this situation. The main purpose of this research is to develop new user-friendly web-based software that uses various techniques to handle missing value(s). Material and Methods: In this study, to assess the performance of the software, various scenarios were tested: 5 variables were normally distributed, different sample sizes (n=1000, 1500, 2000 and 2500), high (r <-0.70 or r> 0.70) and low correlations (-0.30 <r <0.30) among between variables, different number of missing value in variables (5%, 10% and 20% missing data). The missing values were imputed by the developed web software and the results were compared. Thus, the performance of the software under different conditions was evaluated. Shiny, an open source R package was used to develop the web tool. In the developed software, linear regression (LR), random forest (RF), classification and regression trees (CART) and predictive mean matching (PMM) methods were used to impute missing values. In order to achieve more unbiased and reliable results, the 'number of repetitions' and 'number of multiple imputations' sections were used in the software. The normalized root mean squared error (NRMSE) metric was used to assess performance of imputation techniques. The developed web-based application can be accessed free of charge at http://biostatapps.inonu.edu.tr/KDAY/. Results: According to the outputs of the developed web-based application, better results were obtained by LR and PMM models for missing value imputation in datasets with high correlation. For missing value imputation in low-correlated data sets, the models showed similar imputation performances. Conclusion: For the datasets used in this study, when the correlation between the variables is high, the best imputation performance is obtained with the DR and PMM models regardless of the size of the dataset and the percentage of missing values.
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019
In this study, it is aimed to develop a new user-friendly web-based software which can overcome t... more In this study, it is aimed to develop a new user-friendly web-based software which can overcome the difficulties of use due to the limitations in the use stages of parametric and non-parametric tests and can easily use the permutation tests which can be used as an alternative to these tests.Shiny, an open-source R package, is used to develop the recommended web software. In the developed software, by selecting "the Specify Sample Number" tab, the number of samples presented as "Single", "Two" and "More than two" options is selected and analyzes are made by selecting the appropriate data set from the file upload menu.In this study, in order to show the way the software works and to evaluate its outputs, a data set containing 1000 observations with the standard normal distribution of variables consisting of two variables was used. "Two Dependent Sample Permutation Tests" were selected to analyze whether there was any difference between the variables. According to the results, no statistically significant difference was found between the variables.The developed software is a new user-friendly web-based software that can be used to perform the permutation tests in an easy way as an alternative to parametric and non-parametric tests.
Middle Black Sea Journal of Health Science, 2020
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019
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 a...
Middle Black Sea Journal of Health Science
2019 International Artificial Intelligence and Data Processing Symposium (IDAP), 2019
In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal... more In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal distribution of the new data set obtained by applying various mathematical transformations to data sets that do not meet the normal distribution from parametric hypothesis testing conditions. The web based software is developed by Shiny web framework, which is an open source R package. In the web-based software, arcsinh (x), Box-Cox, Exponential, Lambert W (h type), Lambert W (s type), Logarithmic, Square root, Yeo-Johnson data transformation methods are used. The software also allows us to decide on the best conversion for the data set to be transformed by calculating the Pearson P test statistic, which chooses on the best method in the methods used. This is done by selecting the conversion with the smallest Pearson P statistic. In order to evaluate the outputs of the software, a data set with three variables was derived with the Cauchy, gamma, Weibull distributions respectively and 500 samples were used for each distribution. The developed software is novel user-friendly web-based software that enables researchers to get more accurate results in their work and to obtain data transformation methods that provide parametric test assumptions known as more powerful tests.
The Journal of Cognitive Systems, Dec 31, 2020
This study aims to predict mortality status by heart failure and to determine the related factors... more This study aims to predict mortality status by heart failure and to determine the related factors by applying the relational classification method, one of the data mining methods, on the openaccess heart failure data set. Materials and Methods: In this study, the associative classification model has been applied to the open-access data set named "Heart Failure Prediction". The performance of the model was evaluated by accuracy, balanced accuracy, sensitivity, selectivity, positive predictive value, negative predictive value, and F1-score.
Objective: In this study, it is aimed to classify type 2 Diabetes Mellitus (DM), compare the esti... more Objective: In this study, it is aimed to classify type 2 Diabetes Mellitus (DM), compare the estimates of the Artificial Neural Network models and determine the factors related to the disease by applying Multilayer Perceptron (MLP) and Radial Based Function (RBF) methods on the open-access dataset. Material and Methods: In this study, the data set named “Pima Indians Diabetes Database” was obtained from https://www.kaggle.com/uciml/pima-indians-diabetes-database. The dataset contains 768 records with 268 (34.9%) type 2 diabetes patients and 500 (65.1%) people without diabetes, which have 9 variables (8 inputs and 1 outcome). MLP and RBF methods, which are artificial neural network models, were used to classify type 2 DM. Factors associated with type 2 DM were estimated by using artificial neural network models. Results: The performance values obtained with MLP from the applied models were accuracy 78.1%, specificity 81.2%, AUC 0.848, sensitivity 71%, positive predictive value 61.7%,...
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...
Aim: In this study, it is aimed to classify breast cancer and identify related factors by applyin... more Aim: In this study, it is aimed to classify breast cancer and identify related factors by applying deep learning method on open access to breast cancer dataset. Materials and Methods: In this study, 11 variables related to open access to breast cancer dataset of 569 patients shared by the University of Wisconsin were used. The deep learning model for classifying breast cancer was established by a 10-fold cross-validation method. The performance of the model was evaluated with accuracy, sensitivity, specificity, positive/negative predictive values, F-score, and area under the curve (AUC). Factors associated with breast cancer were estimated from the deep learning model. Results: Accuracy, specificity, AUC, sensitivity, positive predictive value, negative predictive value, and F-score values obtained from the model were 94.91%, 91.47%, 0.988, 96.90%, 95.42%, 95.14%, and 96.03%, respectively. In this study, when the effects of the variables in the dataset on breast cancer were evaluate...
Middle Black Sea Journal of Health Science, 2020
Journal of Traditional Medical Complementary Therapies, 2020
Yoğun bakım (YB) ve palyatif bakım (PB) üniteleri yaşam sonu bakımın uygulandığı kliniklerdir. PB... more Yoğun bakım (YB) ve palyatif bakım (PB) üniteleri yaşam sonu bakımın uygulandığı kliniklerdir. PB hizmetlerinin optimal düzeyde verilebilmesi için bu ünitelerde çalışanların PB hakkında yeterli düzeyde bilgi sahibi olması gerekmektedir. Bu çalışmanın amacı, YB ve PB ünitelerinde çalışan doktor ve hemşirelerin PB'ye ilişkin bilgi ve görüşlerinin belirlenmesi ve karşılaştırılmasıdır. Gereç ve Yöntemler: Çalışma; Malatya Eğitim ve Araştırma Hastanesi Reanimasyon YB, Dahiliye YB ve PB ünitelerinde çalışan hekim ve hemşireler ile yüz yüze görüşme yöntemi ile yapılmıştır. Çalışmada veriler, sosyodemografik özellikler formu ve literatür bilgileri doğrultusunda hazırlanan, çalışanların PB'ye yönelik mevcut bilgi ve görüşlerini belirleyici anket formu kullanılarak elde edilmiştir. Bulgular: Çalışmaya katılanların (68 hemşire, 12 doktor) yaş ortalaması 34 olup, çoğunluğunu lisans mezunu kadınlar oluşturmaktaydı. Katılımcıların %80'i eğitimleri sırasında PB eğitimi almadıklarını ve %76,3'ü yapılacak eğitim programlarına ihtiyaç duyduklarını belirtti. YB çalışanlarının %37,5'i, PB çalışanlarının %20'si hospis tanımını bilmediklerini ifade etti. PB çalışanlarının çoğu (%85,1) tedavisi biten hastaların taburculuğunda zorlandıklarını ve %85,5'i PB'de tükenmişlik yaşadıklarını belirtti. YB hemşirelerinin %63,8'i "YB"de PB hizmeti verilmelidir, ifadesine katılmadıklarını ve bu konu hakkında bilgi sahibi olmadıklarını belirtti. Çalışanların tamamına yakını, PB temel eğitiminin üniversite eğitim programlarında zorunlu olması gerektiğini belirtti. Sonuç: YB ve PB ünitesinde çalışan sağlık personelinin "Palyatif bakım ve hospis" kavramları konusunda yeterli bilgiye sahip olmadıkları, bilgi düzeylerinde farklılıklar olduğu ve bu konuda yapılacak eğitim programlarına ihtiyaç duydukları belirlenmiştir. Bu durumun temel lisans eğitimindeki eksikliklerden kaynaklandığı, eğitim müfredatında zorunlu PB eğitim dersinin yer alması ve sertifikalı eğitim programlarının yaygınlaşması gerektiği düşünülmektedir. Anah tar Ke li me ler: Palyatif bakım; yoğun bakım; sağlık personeli; bilgi ABS TRACT Objective: Intensive care (ICU) and palliative care (PD) units are clinics where end-of-life care is applied. In order for PB services to be provided at an optimal level, employees working in these units should have sufficient knowledge about PB. The aim of this study is to determine and compare the knowledge and opinions of doctors and nurses working in the ICU and PD units about palliative care. Material and Methods: Study; Malatya Training and Research Hospital Reanimation YB, Internal Medicine YB and PB were conducted by face to face interviews with physicians and nurses working in the units. In the study, the data were obtained by using the questionnaire form, which was prepared in line with the socio-demographic characteristics form and the literature information, and which determines the current knowledge and opinions of the employees about PD. Results: The average age of the participants (68 nurses, 12 doctors) was 34, most of whom were undergraduate graduates. 80% of the participants stated that they did not receive PD training during their training and 76.3% of them stated that they needed training programs to be carried out. 37.5% of YB employees and 20% of PD employees stated that they do not know the definition of hospis. Most of the PD staff (85.1%) stated that the patients who had completed their treatment had difficulty in discharge and 85.5% of them experienced burnout in PD. 63.8% of the YB nurses stated that they disagree with the statement "PB service should be provided in YB" and they do not have any information about this subject. Almost all of the employees stated that PB basic education should be compulsory in university education programs. Conclusion: It was determined that the health personnel working in the YB and PD unit do not have sufficient information about the concepts of "Palliative care and hospice", there are differences in their knowledge levels and they need training programs to be carried out in this regard. It is thought that this situation is due to the deficiencies in basic undergraduate education, compulsory PB education courses should be included in the education curriculum and certified education programs should become widespread.
Turkiye Klinikleri Journal of Biostatistics, 2019
In a research, it is not desirable that the dataset to be used contains missing value (s) and res... more In a research, it is not desirable that the dataset to be used contains missing value (s) and researchers try to cope with this situation. The main purpose of this research is to develop new user-friendly web-based software that uses various techniques to handle missing value(s). Material and Methods: In this study, to assess the performance of the software, various scenarios were tested: 5 variables were normally distributed, different sample sizes (n=1000, 1500, 2000 and 2500), high (r <-0.70 or r> 0.70) and low correlations (-0.30 <r <0.30) among between variables, different number of missing value in variables (5%, 10% and 20% missing data). The missing values were imputed by the developed web software and the results were compared. Thus, the performance of the software under different conditions was evaluated. Shiny, an open source R package was used to develop the web tool. In the developed software, linear regression (LR), random forest (RF), classification and regression trees (CART) and predictive mean matching (PMM) methods were used to impute missing values. In order to achieve more unbiased and reliable results, the 'number of repetitions' and 'number of multiple imputations' sections were used in the software. The normalized root mean squared error (NRMSE) metric was used to assess performance of imputation techniques. The developed web-based application can be accessed free of charge at http://biostatapps.inonu.edu.tr/KDAY/. Results: According to the outputs of the developed web-based application, better results were obtained by LR and PMM models for missing value imputation in datasets with high correlation. For missing value imputation in low-correlated data sets, the models showed similar imputation performances. Conclusion: For the datasets used in this study, when the correlation between the variables is high, the best imputation performance is obtained with the DR and PMM models regardless of the size of the dataset and the percentage of missing values.
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019
In this study, it is aimed to develop a new user-friendly web-based software which can overcome t... more In this study, it is aimed to develop a new user-friendly web-based software which can overcome the difficulties of use due to the limitations in the use stages of parametric and non-parametric tests and can easily use the permutation tests which can be used as an alternative to these tests.Shiny, an open-source R package, is used to develop the recommended web software. In the developed software, by selecting "the Specify Sample Number" tab, the number of samples presented as "Single", "Two" and "More than two" options is selected and analyzes are made by selecting the appropriate data set from the file upload menu.In this study, in order to show the way the software works and to evaluate its outputs, a data set containing 1000 observations with the standard normal distribution of variables consisting of two variables was used. "Two Dependent Sample Permutation Tests" were selected to analyze whether there was any difference between the variables. According to the results, no statistically significant difference was found between the variables.The developed software is a new user-friendly web-based software that can be used to perform the permutation tests in an easy way as an alternative to parametric and non-parametric tests.
Middle Black Sea Journal of Health Science, 2020
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019
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 a...
Middle Black Sea Journal of Health Science