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Öğe Breast cancer classification using a constructed convolutional neural network on the basis of the histopathological images by an interactive web-based interface(Institute of Electrical and Electronics Engineers Inc., 2019) Arslan A.K.; Yasar S.; Colak C.In this study, it is aimed to develop a system that can provide clinical support to physicians in the diagnosis of breast cancer with open source access artificial intelligence based software. The proposed system was designed using an open source data set for the classification of breast cancer (benign/malignant) on the basis of the histopathological images. In this context, Keras library and convolutional neural networks from deep learning methods were used on the images obtained by staining with hematoxylin and eosin of biopsy specimens taken from breast tissues. Shiny package in the R programming language is employed to develop for the user interface. According to the experimental results obtained from the study, it was determined that the designed system gives promising predictions in the classification of breast cancer and can be used for clinical decision support in the classification of the disease. This designed system can be available at http://biostatapps.inonu.edu.tr/MKSY/ in both English and Turkish. © 2019 IEEE.Öğe Classification of brain tumor types by deep learning with convolutional neural network on magnetic resonance images using a developed web-based interface(Institute of Electrical and Electronics Engineers Inc., 2019) Ucuzal H.; Yasar S.; Colak C.Automated machine learning (AutoML) algorithms developed using deep learning algorithms have been the focus of interest in many studies recently. This study aims to develop a free web-based software based on deep learning that can be utilized in the diagnosis and detection of brain tumors (Glioma/Meningioma/Pituitary) on T1-weighted magnetic resonance imaging. The Keras library, which is used in Python programming language, is utilized in the construction of the deep learning algorithm in this software. The experimental results show that this software can be used for the detection and diagnosis of three types of brain tumors. This developed web-based software can be publicly available at http://biostatapps.inonu.edu.tr/BTSY/ in both English and Turkish. © 2019 IEEE.Öğe Comparison of Propofol and Ketamine-Propofol Mixture (Ketofol) on Laryngeal Tube-Suction II Conditions and Hemodynamics: A Randomized, Prospective, Double-Blind Trial(2013) Ozgul U.; Begec Z.; Karahan K.; Ali Erdogan M.; Said Aydogan M.; Colak C.; Durmus M.Objective: The aim of our study is to compare the effect of ketamine-propofol mixture (ketofol) and propofol on the laryngeal tube-Suction II (LTS II) insertion conditions and hemodynamics. Methods: Eighty American Society of Anesthesiologists class 1 and 2 patients were divided into 2 random groups to receive either 1 ?g/kg remifentanil and propofol 2 mg/kg in Group P (n = 40), or 1 ?g/kg remifentanil and ketofol (using a 1:1 single syringe mixture of 5 mg/mL ketamine and 5 mg/mL propofol) in Group K (n = 40) before induction of anesthesia. After induction, LTS II was inserted. Heart rate and noninvasive blood pressure were recorded before induction of anesthesia (t0); immediately following induction (t1); immediately after LTS II insertion (t2); and 3 minutes (t3), 5 minutes (t4), and 10 (t5) minutes after LTS II insertion. Conditions of insertion of LTS II were assessed and scored 1 to 3 using 6 variables as follows: mouth opening, swallowing, coughing, head and body movements, laryngospasm, and ease of LTS II insertion by the same experienced anesthesiologist who did not know the agents. LTS II insertion summed score was prepared depending upon these variables. Results: In regard to LTS II insertion summed score, Group K was more favorable than Group P (P < 0.05). Apnea duration was longer in Group P (385.0 seconds [range = 195.0-840.0 seconds]) compared with Group K (325.50 seconds [range = 60.0-840.0 seconds]) but this was not statically significant. The heart rate values were significantly lower at all measurement intervals in both groups compared with the baseline values (P < 0.05). There was no difference in heart rate between Group P and Group K. The mean arterial pressure values were significantly lower at all measurement intervals in Group P compared with baseline values (P < 0.05). In Group K, the mean arterial pressure values were significantly lower at all measurement intervals compared with the baseline values, except t2 (P < 0.05). There was a significant difference between Group P and Group K in terms of mean arterial pressure at t3 (P < 0.05). Conclusions: We found that ketofol provided better insertion summed score for LTS II than propofol, with minimal hemodynamic changes. © 2013 The Authors.Öğe Effects of dexmedetomidine and midazolam on motor coordination and analgesia: A comparative analysis(2013) Aydogan M.S.; Parlakpinar H.; Ali Erdogan M.; Yucel A.; Ucar M.; Sa?ir M.; Colak C.Objective: We compared the effects of 2 sedative drugs, dexmedetomidine and midazolam, on motor performance and analgesic efficacy in a rat model. Materials and methods: Rats were randomly divided into the following 4 groups on the basis of the treatment received. The first group received 83 ?g/kg/min midazolam; the second, 1 ?g/kg/min dexmedetomidine; the third, 83 ?g/kg/min morphine; and the fourth was a control group. The rats were measured motor coordination and pain reflexes by using rotarod, accelerod, hot plate, and tail flick tests. Results: At all the tested speeds, the midazolam-injected rats remained on the rotarod longer than did the dexmedetomidine-injected rats. Furthermore, in the 10-minute accelerod test, the midazolam-injected rats remained for a longer duration than did the dexmedetomidine-injected rats. The latency time for the hot plate test was significantly higher at 10 minutes and 20 minutes in the dexmedetomidine group than in the midazolam group. Further, the latency time at 10 minutes for the tail flick test was greater in the dexmedetomidine group than in the midazolam group. Conclusions: In this rat model, midazolam results in faster recovery of motor coordination performance when compared with dexmedetomidine. © 2013 The Authors.Öğe Falls from height: A retrospective analysis(Second Affiliated Hospital, Zhejiang University School of Medicine, 2021) Turgut K.; Sarihan M.E.; Colak C.; Güven T.; Gür A.; Gürbüz S.BACKGROUND: Emergency services manage trauma patients frequently and falls from height comprise the main cause of emergency service admissions. In this study, we aimed to analyse the demographic characteristics of falls from height and their relationship to the mortality. METHODS: A total of 460 patients, who admitted to the Emergency Department of Inonu University between November 2011 and November 2014 with a history of fall from height, were examined retrospectively. Demographic parameters, fall characteristics and their effect to mortality were evaluated statistically. RESULTS: The study comprised of 292 (63.5%) men and 168 (36.5%) women patients. The mean age of all patients was 27±24.99 years. Twenty-six (5.6%) patients died and the majority of them were in ?62 years old group. The highest percentage of falls was at 0–5 years age group (28.3%). People fell mainly from 1.1–4 metres(m) level (46.1%). The causes of falls were ordered as unintentional (92.2%), workplace (8.1%) and suicidal (1.7%). Skin and soft tissue injuries (37.4%) were the main traumatic lesions. CONCLUSION: Age, fall height, fall place, linear skull fracture, subarachnoidal hemorrhage, cervical fracture, thoracic vertebra fracture and trauma scores had statistically significant effect on mortality. The casualties died because of subarachnoid hemorrhage mostly. © 2018 World Journal of Emergency MedicineÖğe Generalization of Korovkin type approximation by appropriate random variables & moments and an application in medicine(2011) Gürcan M.; Colak C.This paper is mainly connected with the approximation properties of the positive linear operators which are representative expectation of some random variables. Firstly, it was introduced the generalizations of Korovkin type approximation theorem via the probabilistic methods. Also, it was computed the rates of convergence by means of modulus of continuity and moments of some random variables. Finally, some important results of the approximation theory were obtained; one of these important results is the difference between using appropriate operator and function and function's derivatives. A medical application performed on hypothetical data to the statistical significance of the findings has been mentioned. © 2011 Pakistan Journal of Statistics.Öğe An intelligent system for the classification of postoperative pleural effusion between 4 and 30 days using medical knowledge discovery(Scientific Publishers of India, 2017) Guldogan E.; Arslan A.K.; Colak M.C.; Colak C.; Erdil N.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, Naïve Bayes, Bayesian network and Random Forest algorithms were utilized. Accuracy and area under receiver operating characteristics (ROC) curve (AUC) were calculated as evaluation metrics. Results: In the preprocessing step, 85 outlier observations were removed from the study. The rest of the data consisted of 2224 subjects: 2149 of these individuals were in non-PE group, and the 75 were in PE group. Random Forest yielded the best classification performance with 97.45% of accuracy and 0.990 of AUC for 0.7 of the optimal split ratio by Grid search algorithm. Conclusion: The achieved results pointed out that the best classification performance was obtained from the RF ensemble model. Therefore, the suggested intelligent system can be used as a clinical decision making tool. © 2017, Scientific Publishers of India. All rights reserved.Öğe An Interactive Web Tool for Classification Problems Based on Machine Learning Algorithms Using Java Programming Language: Data Classification Software(Institute of Electrical and Electronics Engineers Inc., 2019) Percin I.; Yagin F.H.; Arslan A.K.; Colak C.Classification analysis is a frequently used approach in fields such as biomedical, bioinformatics, medical and engineering. In the field of health, it has become common to classify diseases based on risk factors by machine learning methods and to determine the effect sizes of these risk factors on the disease. There are many analysis tools used to guide researchers in classification analysis. While some of these tools are commercial and provide basic methods for classification analysis, some offer advanced analysis techniques and are desktop applications such as the WEKA environment.The WEKA environment includes comprehensive tools for classification analysis. However, use of the WEKA environment can be difficult and time-consuming, especially when a quick assessment is essential for users who do not have WEKA tool on their computer (doctors, etc.). Therefore; fast, comprehensive, free and easy to use analysis tool is required. The purpose of this study is to develop a user-friendly web tool (Data Classification Software; DCS) based on the classification algorithms of WEKA tool in Java programming language.The data classification software can be used on any device with an internet connection, which is independent of the any operating systems. In the developed web-based tool, data preprocessing module consists of missing value assignment, variable type conversion and normalization-standardization methods. Classification module encapsulates random forest, Naive Bayes, Bayes Network, j48, sequential minimal optimization, a rule and attribute selected classifier algorithms. This web tool can be accessed free of charge at http://biostatapps.inonu.edu.tr/DCS/. © 2019 IEEE.Öğe Malaria cases in Malatya during the past seven years(2007) Karaman U.; Atambay M.; Yaşar S.; Colak C.; Miman O.; Daldal N.Malaria can be seen in every region inhabited by human blood-sucking Anopheles and species of disease-causing Plasmodium. Since the region is on the crossroads of other cities where malaria is more widespread and it has a population of seasonal workers and an increasing number of tourists during the summer, additional imported cases may also be detected in the Malatya region. The aim of this study was to determine the state of malaria for the past seven years in Malatya. According to the records of the Malaria Control Unit of the Health Directorate of the Malatya province, 189 positive patients were reported during the seven years from 1999-2005. Of these cases, 186 (98.4%) were P. vivax, while 3 (1.6%) were imported cases of P. falciparum malaria. The rate of positivity was found to be 58.2% in male patients and 41.8% in female patients. Consequently, malaria can be said to persist as a health problem in Malatya region. It was concluded that people in the region should be informed about malaria and the ways to protect themselves.Öğe Open Source Web-Based Software to Evaluate Normal Distribution: Normality Assessment Software(Institute of Electrical and Electronics Engineers Inc., 2019) Arslan A.K.; Tunc Z.; Colak C.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. © 2019 IEEE.Öğe Open-Source Web-Based Software for Performing Permutation Tests(Institute of Electrical and Electronics Engineers Inc., 2019) Tunc Z.; Yasar S.; Colak C.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. © 2019 IEEE.Öğe Prediction of melanoma from dermoscopic images using deep learning-based artificial intelligence techniques(Institute of Electrical and Electronics Engineers Inc., 2019) Kaplan A.; Guldogan E.; Colak C.; Arslan A.K.Recently, hospitals and health care institutions have increasingly been addressing clinical decision support systems (CDSS), which can offer specific patient assessments or recommendations to physicians and health care professionals. It is very useful to develop CDSS which can help physicians to make meaningful and correct decisions by using existing data or image sets. Also, CDSS increases the diagnostic accuracy of diseases, provides significant facilities in precision medicine applications, increases operating efficiency of hospitals and reduces costs. In this context, the proposed project intends to create a model using pre-Trained networks (i.e. VGG-16,) based on deep learning (DL) that can successfully predict the melanoma using dermoscopic images. The current study provides clinical support to physicians in the medical decision-making process for the diagnosis of melanoma. © 2019 IEEE.Öğe The prevalence of Microsporidium among adult patients admitted to the parasitology laboratory at the Inonu University Turgut Ozal Medical Center(2008) Atambay M.; Karaman U.; Daldal N.; Colak C.Microsporidium can cause acute and self-restricted diarrhea cases among immunocompetent patients. The aim of this study was to investigate the presence of intestinal parasites and Microsporidium in patients presenting at the internal diseases polyclinic with some digestive system complaints but no immune suppressive problems, and to detect whether it has anything to do with the complaints. A total of 781 fecal samples were investigated for intestinal parasites and Microsporidium. Intestinal parasites were found in 16.11% and Microsporidium in 6.5%. A significant correlation was observed between the presence of intestinal parasites other than Microsporidium and dyspepsia, while in the case of Microsporidium, a significant frequency of dyspepsia and fatigue was observed. It was found that the presence of Microsporidium does not differ by age and gender. From the findings, it was concluded that patients with digestive system complaints should be examined for Microsporidium in addition to intestinal parasites, and the symptoms of dyspepsia and a lack of appetite should especially be given more careful attention.Öğe The prevalence of Microsporidium among patients given a diagnosis of cancer(2008) Karaman U.; Atambay M.; Daldal N.; Colak C.The aim of this study was to determine the frequency of Microsporidium among patients given a diagnosis of cancer. For this purpose fecal samples from 320 patients aged 23.60+/-23.00 years were examined using native-Lugol and sedimentation methods and evaluated with modified trichrome, trichrome, and calcofluor dyes. Moreover a control group of 320 non-cancer patients was set up. While 10.9% of the patient group was found to have Microsporidium, only 5.6% of the control group did. Comparison between the control and patient groups in terms of presence of Microsporidium revealed a statistically significant difference. The analysis of a possible relation between intestinal parasites and the presence of Microsporidium revealed a statistically significant correlation between Microsporidium and Blastocystis hominis (P < 0.05). The frequencies of intestinal parasites in the control group and the patient group were found to be 17.8% and 18.1%, respectively. From the findings it was concluded that presence of intestinal parasites and Microsporidium in cancer patients can cause critical problems and adversely affect the therapy. Moreover it was suggested that cancer patients should be informed about regular feces examination and protection against parasites in order to improve their life standards and protect them against parasite infections during treatment.Öğe A Web-Based Application for Identifying Objects in Images: Object Recognition Software(Institute of Electrical and Electronics Engineers Inc., 2019) Ucuzal H.; Balikci Cicek A.G.I.; Arslan A.G.A.K.; Colak C.Object recognition is a computer vision technique for identifying objects in images or videos. Object recognition is an important output of deep learning and machine learning algorithms. For this purpose, open source, free and artificial intelligence based Object Recognition Software has been developed in order to perform object recognition operation easily.In creating this web-based software, Darkflow and Tensorflow libraries are used which are based on deep learning based Python programming language and allow the design of interactive web based applications. While performing object recognition analysis in the developed software, CNN (Convolutional Neural Networks) multiple convolution layers are uncovered hidden and useful features obtained by various calculation methods. With CNN, objects are classified, objects are detected, and objects are determned by image segmentation. A pre-trained model from COCO, a large-scale object detection, partitioning and image dataset, is used to see how the web-based software work and to evaluate the analysis outputs. Object recognition analysis is applied to ten images from this data set. According to the object recognition analysis results of the ten images, the calculated accuracy rates is examined and it is found that this web based software which is developed as open source and free access gives successful estimations in object recognition.In order to see how the web-based software works and to evaluate the analysis outputs, a pre-trained model was used from COCO (Common Objects in Context) which is a large scale object detection, partitioning and image dataset. Object recognition analysis was applied to ten images from this data set. When the accuracy ratio of the ten images calculated according to the object recognition analysis result is examined, it is determined that this web based software which is developed as open source and free access gives successful predictions in object recognition.The developed software is new user-friendly web-based software that can easily identify objects in images and discriminatory from each other objects. In the following studies, in order to increase the diagnostic accuracy of the objects in the images, it is suggested that the softwares that uses deeper neural networks should be developed and the necessary infrastructure to detect the defects in the medical images can be developed. © 2019 IEEE.
