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Öğe A novel approach to the diagnostic assessment of carpal tunnel syndrome based on the frequency domain of the compound muscle action potential(Walter De Gruyter Gmbh, 2020) Alcan, Veysel; Kaya, Hilal; Zinnuroglu, Murat; Karatas, Gulcin Kaymak; Canal, Mehmet RahmiConventional electrophysiological (EP) tests may yield ambiguous or false-negative results in some patients with signs and symptoms of carpal tunnel syndrome (CTS). Therefore, researchers tend to investigate new parameters to improve the sensitivity and specificity of EP tests. We aimed to investigate the mean and maximum power of the compound muscle action potential (CMAP) as a novel diagnostic parameter, by evaluating diagnosis and classification performance using the supervised Kohonen self-organizing map (SOM) network models. The CMAPs were analyzed using the fast Fourier transform (FFT). The mean and maximum power parameters were calculated from the power spectrum. A counter-propagation artificial neural network (CPANN), supervised Kohonen network (SKN) and XY-fused network (XYF) were compared to evaluate the classification and diagnostic performance of the parameters using the confusion matrix. The mean and maximum power of the CMAP were significantly lower in patients with CTS than in the normal group (p < 0.05), and the XYF network had the best total performance of classification with 91.4%. This study suggests that the mean and maximum power of the CMAP can be considered as less time-consuming parameters for the diagnosis of CTS without using additional EP tests which can be uncomfortable for the patient due to poor tolerance to electrical stimulation.Öğe ASSESSING THE EFFECT OF AGE-RELATED SENSORY INPUT CHANGES ON POSTURAL SWAY IRREGULARITY(2023) Alcan, VeyselAge-related decline in sensory inputs in elderly people leads to postural instability that increases irregularity of postural sway. This study aimed to examine the effect of visual or somatosensory inputs on postural sway irregularity in the elderly by using machine learning (ML). The feature set was extracted from entropy measurements including sample, fuzzy, distribution, conditional, and permutation. Then, the variables were classified by ML including support vector machines (SVM), k-nearest neighbors (k-NN), and linear discriminant analysis (LDA) algorithms. Classification performances were compared with the confusion matrix. For the elderly, in the eyes closed condition on an unstable surface, the SVM algorithm achieved higher accuracy (77%), sensitivity (72%), specificity (85%), and precision (83%) for the cv dataset. For young, SVM also achieved high accuracy (86%), sensitivity (87%), specificity (84%), and precision (84%). For the elderly, under the eyes open on unstable surface conditions, the SVM exhibited an accuracy of 79%, sensitivity of 75%, specificity of 72%, and precision of 75%. However, for young, it did not reveal good results for both surfaces. In conclusion, the findings suggest that older people adapt their postural control mechanisms, relying more on somatosensory inputs. ML algorithms with entropy-based features can give insights into age-related differences in postural control.Öğe Assessment of the Health Complaints among White-Collar and Blue-Collar Workers Using the Electronic Health Records(Zonguldak Bulent Ecevit University, 2023) Alcan, Veysel; Doğru, CanerElectronic health records (EHRs) are a useful tool to determine the causes and trends of work-related diseases in terms of periodic check-ups or emergency interventions at the workplace. To detect and prevent work-related diseases, EHRs could be important determinants for assessing interactions between health complaints and work-related factors. This study aimed to address the prevalence of diseases that cause potentially work-related diseases and the relationship between blue-collar/white-collar work status, by using EHRs. We retrospectively analyzed the clinical and demographic data from EHRs (46 white-collar and 94 blue-collar) by using descriptive and correlation statistic tests. We found that type 2 diabetes, influenza, acute pharyngitis, and liver fat had a higher prevalence among blue-collar workers while urinary infection and myalgia had a higher prevalence among white-collar workers. The work status had a very weak positive correlation with type 2 diabetes (r=0.236, p=0.005) and had a very weak negative correlation with myalgia (r=-0.167, p=0.048) and urinary infection (r= -0.248, p= 0.003). Consequently, the present study provided that the work status and EHRs are important determinants for assessing interactions between health complaints and work-related factors that were attributable to specific work status such as blue-collar and white-collar.Öğe Awareness and attitudes towards infectious diseases among teachers and administrators: Evaluation of health-related school program and practices(Elsevier Inc, 2024) Aksun, Kaan; Alcan, VeyselBackground: Schools play a crucial role in promoting health education and awareness about infectious diseases. This study aims to examine teachers' and administrators' awareness and attitudes towards infectious diseases and their specific health -related applications. Methods: This study used a new scale to collect survey data from 435 teachers and administrators. The validity and reliability of the scale were assessed by factor analysis. Pearson correlation and regression analysis were conducted to explore the relationships between variables. T -tests and one-way ANOVA were employed for group comparisons. Results: The findings revealed a concerning skepticism among a significant portion of participants towards the effectiveness of vaccines in ending epidemics and a lack of health education activities in schools. Significant differences were observed in the scores for physical measures, educational activities, awareness, observation, and attitudes based on school type and ownership of certificates (p <= 0.05). Conclusions: This study highlights the need for continuous education and awareness -raising efforts to develop sustainable school health practices. Integrating diverse health professionals into school health management teams can enhance health services in educational settings. The present study also emphasizes the importance of comprehensive health education in understanding infectious diseases, preventive measures, and proper hygiene practices. (c) 2024 Australasian College for Infection Prevention and Control. Published by Elsevier B.V. All rights reserved.Öğe Classification of radiographic and non-radiographic axial spondylarthritis in pelvic radiography using deep convolution neural network models(Springer, 2025) Kahveci, Abdulvahap; Alcan, Veysel; Ucar, Murat; Gumustepe, Alper; Bilgin, Esra; Sunar, Ismihan; Ataman, SebnemDiscriminating radiographic axial spondyloarthritis (r-axSpA) from nonradiographic axial spondyloarthritis (nr-axSpA) using pelvic radiographs is challenging, especially for inexperienced clinicians. This study aims to perform deep convolution neuronal network (CNN) models to aid in this diagnostic challenge by using their radiographs. Six-hundred sacroiliac joint exams (300 pelvic radiographs) of patients from axSpA cohort were enrolled (screened between Jan 2010 and Jan 2020). All radiographs were examined and graded by a blinded expert rheumatologist. Four CNN models (VGG16, ResNet, DenseNet, and MobileNet) were proposed by combining them with the YOLOv7 object detection algorithm to mark the sacroiliac joints. The classification results of CNNs were evaluated by performance metrics [accuracy, AUROC (area under the receiver operating characteristic curve)]. The VGG16 model with the YOLOv7 algorithm yielded the best performance [accuracy of 83.8% (95% CI; 73.3-92.9%)]. The accuracy values of other models were 70.7% (58.3-82.7%), 77.1% (65.1-87.3%), and 71.8% (59.0-83.1%) for ResNet, DenseNet, and MobileNet, respectively. In the ROC analysis, the AUC value of the VGG16 model (AUC = 0.882) was higher than other CNNs (AUCs = 0.836, 0.808, and 0.787; DenseNet, ResNet, and MobileNet, respectively). This paper revealed deep learning architectures were able to differentiate r-axSpA from nr-axSpA on pelvic radiographs. Hereby, these models might be used as a clinical decision support system in clinical practice.Öğe Coherence Analysis of Surface Electromyography Signals of Facial Mimic Muscles(Ieee, 2024) Alcan, Veysel; Seker, MehmetThis study aimed to perform a coherence analysis of surface electromyography (EMG) signals to investigate neural control mechanisms and coordination of facial expression muscles. A publicly available data set containing surface EMG data from the zygomaticus major (ZM), orbicularis oris (OO), and orbicularis oculi (OOc) muscles was used in the study. Experimental protocols included facial movements without gum chewing (condition A) and with chewing gum (condition B). Coherence analysis was used to understand the frequency-domain relationships between EMG signals. The results were compared statistically between the two conditions. Significant differences in coherence values were observed between conditions for the peak coherence value for ZM-OOc muscle pairs (p < 0.05). Coherence estimates for ZM-OOc showed a slight contribution at 10-60 Hz in condition A, while in condition B they showed a very significant contribution towards the 70-90 Hz band and reached a high value peak. This points to different neural control mechanisms and an increase in the synergetics of the muscles, especially with a mechanical effect such as chewing gum on the ZM-OOc muscle during various facial expressions. In conclusion, this study provided important information about neural control mechanisms and coordination patterns through the coherence analysis of surface EMG signals in facial expression muscles. The findings support targeted rehabilitation for motor disorders in facial muscles.Öğe Comparison of Interpolation Methods in the Diagnosis of Carpal Tunnel Syndrome(Galenos Publ House, 2018) Alcan, Veysel; Zinnuroglu, Murat; Karatas, Gulcin Kaymak; Bodofsky, ElliotBackground: Diagnosis of carpal tunnel syndrome is based on clinical symptoms, examination findings, and electrodiagnostic studies. For carpal tunnel syndrome, the most useful of these are nerve conduction studies. However, nerve conduction studie can result in ambiguous or false-negative results, particularly for mild carpal tunnel syndrome. Increasing the number of nerve conduction studie tests improves accuracy but also increases time, cost, and discomfort. To improve accuracy without additional testing, the terminal latency index and residual latency are additional calculations that can be performed using the minimum number of tests. Recently, the median sensory-ulnar motor latency difference was devised as another way to improve diagnostic accuracy for mild carpal tunnel syndrome. Aims: The median sensory-ulnar motor latency difference, terminal latency index, and residual latency were compared for diagnostic accuracy according to severity of carpal tunnel syndrome. Study Design: Diagnostic accuracy study. Methods: A total of 657 subjects were retrospectively enrolled. The carpal tunnel syndrome group consisted of 546 subjects with carpal tunnel syndrome according to nerve conduction studie (all severities). The control group consisted of 121 subjects with no hand symptoms and normal nerve conduction studie. All statistical analyses were performed using SAS v9.4. Means were compared using one-way ANOVA with the Bonferroni adjustment. Sensitivity, specificity, positive predictive value, and negative predictive value were compared, including receiver operating characteristic curve analysis. Results: For mild carpal tunnel syndrome. the median sensory-ulnar motor latency difference showed higher specificity and positive predictive value rates (0.967 and 0.957, respectively) than terminal latency index (0.603 and 0.769, respectively) and residual latency(0.818 and 0.858, respectively). The area under the receiver operating characteristic was highest for the median sensory-ulnar motor latency difference (0.889), followed by the residual latency (0.829), and lastly the terminal latency index (0.762). Differences were statistically significant (median sensory-ulnar motor latency difference being the most accurate). For moderate carpal tunnel syndrome, sensitivity and specificity rates of residual latency (0.989 and 1.000) and terminal latency index (0.983 and 0.975) were higher than those for median sensory-ulnar motor latency difference (0.866 and 0.958). Differences in area under the receiver operating characteristic curve were not significantly significant, but median sensory-ulnar motor latency difference sensitivity was lower. For severe carpal tunnel syndrome, residual latency yielded 1.000 sensitivity, specificity, positive predictive value, negative predictive value and area beneath the receiver operating characteristic curve. Differences in area under the receiver operating characteristic curve were not significantly different. Conclusion: The median sensory-ulnar motor latency difference is the best calculated parameter for diagnosing mild carpal tunnel syndrome. It requires only a simple calculation and no additional testing. Residual latency and the terminal latency index are also useful in diagnosing mild to moderate carpal tunnel syndrome.Öğe Current developments in surface electromyography(Tubitak Scientific & Technological Research Council Turkey, 2023) Alcan, Veysel; Zinnuroglu, MuratBackground/aim: Surface electromyography (surface EMG) is a primary technique to detect the electrical activities of muscles through surface electrodes. In recent years, surface EMG applications have grown from conventional fields into new fields. However, there is a gap between the progress in the research of surface EMG and its clinical acceptance, characterized by the translational knowledge and skills in the widespread use of surface EMG among the clinician community. To reduce this gap, it is necessary to translate the updated surface EMG applications and technological advances into clinical research. Therefore, we aimed to present a perspective on recent developments in the application of surface EMG and signal processing methods. Materials and methods: We conducted this scoping review following the Joanna Briggs Institute (JBI) method. We conducted a general search of PubMed and Web of Science to identify key search terms. Following the search, we uploaded selected articles into Rayyan and removed duplicates. After prescreening 133 titles and abstracts, we assessed 91 full texts according to the inclusion criteria. Results: We concluded that surface EMG has made innovative technological progress and has research potential for routine clinical applications and a wide range of applications, such as neurophysiology, sports and art performances, biofeedback, physical therapy and rehabilitation, assessment of physical exercises, muscle strength, fatigue, posture and postural control, movement analysis, muscle co-ordination, motor synergies, modelling, and more. Novel methods have been applied for surface EMG signals in terms of time domain, frequency domain, time-frequency domain, statistical methods, and nonlinear methods. Conclusion: Translating innovations in surface EMG and signal analysis methods into routine clinical applications can be a helpful tool with a growing and valuable role in muscle activation measurement in clinical practices. Thus, researchers must build many more interfaces that give opportunities for continuing education and research with more contemporary techniques and devices.Öğe DETERMINATION OF MALIGNANT MELANOMA BY ANALYSIS OF VARIATION VALUES(Murat Yakar, 2019) Esim, Ahmet Kürşat; Kaya, Hilal; Alcan, VeyselMelanoma is a serious disease associated with mutation-based cancer cells. Genetic structure and hereditary condition play important role to understand the underlying reasons of the diseases caused by Deoxiribole Nucleic Acid (DNA). In order to identify mutation carriers and to analyze disease, researchers tend to find various gene determinations methods. Nowadays, Next Generation Sequencing (NGS) is emerging as a valuable and powerful platform to detect gene-based diseases by entiring human genome. In this study, we aimed to propose a bioinformatics application workflow to distinguish between insertions/deletions and somatic/germline mutations, by using NGS methods. We carried this study out on a data set containing 100 human genomes data (20 training, 80 testing) for the detection of Malignant Melanoma. We found that the results of diagnosis performance were 92.50% accuracy, 94.03% precision, 96.92% sensitivity and 95.45% F1 score. These results show the potential for proposed application based on NGS to improve Melanoma detection. © 2019, Murat Yakar. All rights reserved.Öğe Development of Electronic Health Record System Based on Carpal Tunnel Syndrome(Gazi Univ, 2019) Talan, Mehmet Ibrahim; Canal, Mehmet Rahmi; Alcan, Veysel; Kaya, Hilal; Zinnuroglu, MuratPhysical examination, clinical tests and electrophysiological methods are used in the diagnosis of carpal tunnel syndrome (CTS). However, in practice there are no standard clinical and electrophysiological tests for clinics and laboratories. Therefore, data fragmentation or incompatibilities may occur in Electronic Health Record (EHR) systems. Furthermore, secondary use and different biomedical research targets are not considered in these EHR systems. During routine documentation, incomplete, incorrect, inconsistent data entry and incorrect coding can be done. This study aimed to develop an EHR system that could be used in different clinics and centers in diagnosis of CTS, thus creating a standardized, high quality, predictive, preventive, personalized and real-time participatory CTS biomedical data warehouse. The CTS-based EHR system was developed using Microsoft Visual Studio C # programming language. Also during a new patient record, the system was supported by a clinical decision support system (CDS S) based on the data mining methods using WEKA program for pre-diagnosis of the CTS. This EHR system also allows clinical and electrophysiological test results as well as genetic and environmental variants to be integrated into a single database within the framework of precision medicine approachment. In addition, this system can provide a large scale accurate and complete data warehouse for secondary use purposes.Öğe Effects of Sensory Input Interactions on Components of Nonlinear Dynamics of Postural Sway in Aging(Routledge Journals, Taylor & Francis Ltd, 2024) Alcan, VeyselPostural control involves complex nonlinear dynamics influenced by the interaction and adaptation of different sensory inputs. However, it is not how these inputs interact with one another due to the complex complications associated with aging, particularly concerning the nonlinear dynamics of postural sway. This study aimed to examine how different sensory inputs, surface conditions, and aging factors to influence postural control mechanisms between young and older by investigating the nonlinear dynamics of postural control using the stabilogram diffusion analysis (SDA) and entropy methods. SDA parameters were much greater on foam surfaces than on firm surfaces for both groups in eyes-open and eyes-closed conditions (p <= 0.05). For older subjects, there were significant differences in entropy values between firm and foam surfaces (p <= 0.05) but no significant difference between eyes conditions (p > 0.05). For both SDA and entropy parameters, surface and age interaction potentially revealed significant differences between young and older subjects (p <= 0.05) than eyes and age interaction. The present study provided insight into uncovering the complex relationships between sensory inputs, surface conditions, age, and their potential interaction effects on postural control mechanisms that could mitigate falls and alleviate the fear of falling, particularly in older populations.Öğe Electromyographic analysis of the traditional and spin throwing techniques for goalball games related to ball velocity for selected upper extremity muscles(BMC Sports Science, Medicine and Rehabilitation, 2024) Gökçen, Ayşenur; İnce, Gonca; Alcan, VeyselGoalball is a popular sport among visually impaired individuals, offering many physical and social benefits. Evaluating performance in Goalball, particularly understanding factors influencing ball velocity during throwing techniques, is essential for optimizing training programs and enhancing player performance. However, there is limited research on muscle activation patterns during Goalball throwing movements, needing further investigation to address this gap. Therefore, this study aims to examine muscle activity in sub-elite visually impaired Goalball players during different throwing techniques and visual conditions, focusing on its relationship with ball velocity. Methods: 15 sub-elite Goalball players (2 female, 13 males; mean age of 20.46 ± 2.23 years) participated in the study. Muscle activity was evaluated with the Myo armband, while ball velocity was measured using two cameras and analyzed with MATLAB software. Different visual conditions were simulated using an eye band, and the effects of these conditions on muscle activation and ball velocity were examined. Results: The flexor muscles were found to be more active during the spin throw techniques with the eyes open (p = 0.011). The extensor muscles were found to be more active in the eyes-closed spin throw techniques compared to the eyes-open position (p = 0.031). Ball velocity was found related to the flexor muscles. Interestingly, no significant differences in ball velocity were observed between different throwing techniques or visual conditions (p > 0.05). Conclusions: Ball velocity, one of the performance indicators of the athlete, is primarily related to upper extremity flexor muscle strength rather than visual acuity. It has less visual acuity, but an athlete with more upper-extremity flexor muscle strength will have an advantage in Goalball game. The spin throw technique, which is reported to provide a biomechanical advantage for professional players in the literature, did not provide an advantage in terms of ball velocity for the sub elite players evaluated in our study. This knowledge can inform the development of targeted training programs aimed at improving technique and enhancing ball velocity in Goalball players.Öğe Enhancing age-related postural sway classification using partial least squares-discriminant analysis and hybrid feature set(Springer London Ltd, 2024) Alcan, VeyselFeature sets in a machine learning algorithm can have an impact on the robustness, interpretability, and characterization of the data. To detect age-related changes, traditional linear methods for analyzing center of pressure (COP) signals offer limited insight into the complex nonlinear dynamics of postural control. To overcome this limitation, a novel approach that combines a partial least squares-discriminant analysis (PLS-DA) classifier with the nonlinear dynamics of COP time series was proposed. Three small feature sets were compared: time-domain features alone, entropy-based features alone, and a hybrid approach incorporating both types of features. The performance of the PLS-DA model was assessed in four different eyes and surface conditions by using the accuracy, sensitivity, selectivity, precision metrics, and ROC curves. The results indicated that the PLS-DA model utilizing the hybrid feature set achieved significantly higher accuracy than the time-domain and entropy-based feature sets. The best classification performance was observed when the eyes were open on a compliant surface, with an overall accuracy of 89% for training and 88% for cross-validation. For the old group, while the results indicated 93% sensitivity, 94% specificity, and 93% precision in the training, the results revealed 88% sensitivity, 93% specificity, and 91% precision in cross-validation. Notably, the hybrid feature set yielded an AUC value of 0.96, indicating a superior performance. This study emphasizes the robust classification capabilities of PLS-DA for age-related postural changes and highlights the effectiveness of utilizing a small hybrid feature set to improve classification accuracy and reliability.Öğe Evaluating electronic and structural properties of Au and Cu substituted AgCl electrode for application in surface electromyography(Elsevier Sci Ltd, 2021) Alcan, Veysel; Ozkendir, Osman MuratThe material content of electrodes is very much important for improving the signal quality of surface electromyography (sEMG) in various environments, in particular, long-term monitoring. The electronic and structural properties of silver/silver chloride (Ag/AgCl), a popular biopotential electrode for sEMG recording, were studied under different conditions by X-ray absorption fine structure (XAFS) spectroscopy calculations. The effects of substitution of good-conducting elements (Cu and Au) on Ag coordination were tested at different temperatures as well as possible defect conditions. In the Au-substituted AgCl material, an extension of the Ag K-edge spectra was detected due to the rich quantum symmetry of Au valence level. Hence, it was determined that Au atoms bond with Cl atoms stronger than Ag atoms. Additionally, it was determined that Au atoms also changed the ionic properties of Ag atoms by losing Ag-Cl bonds.Öğe Fizyoterapi ve Rehabilitasyon Eğitiminde Kanıta Dayalı Uygulama Yaklaşımının Sistematik Olarak Gözden Geçirilmesi(Hüseyin SELVİ, 2020) Alcan, VeyselFizyoterapistlerden kişilerin sağlık sonuçlarını en üst düzeye çıkarmak için araştırma kanıtlarını klinik karar verme süreçlerine dâhil etmeleri beklenmektedir. Fakat yapılan araştırmalarda bilgi ve yeterlilik düzeylerindeki eksiklik, tutum değiştirme ile ilgili sorunlar ve zaman yetersizliği gibi engellerden dolayı rutin uygulamada kanıta dayalı uygulama (KDU) yaklaşımının yeterli ölçüde kullanılmadığı rapor edilmiştir. Akademik programlar, KDU temelli fizyoterapi ve rehabilitasyon becerilerini geliştirmede ve daha sonra pratikte kullanımını desteklemede en önemli role sahiptir. Eğitim programlarının KDU temelli bilgi ve beceri stratejileri, fizyoterapideki akredite ulusal ve uluslararası kuruluşların beklentileri, sektör ve iş gücü piyasasının beklentilerini karşılayabilecek dinamik bir içeriğe sahip olmalıdır. Bu yüzden fizyoterapistlerin klinik karar verme stratejilerinde, klinik uygulamalarında hangi test ve değerlendirme ölçüm araçlarının etkin ve uygun olacağını belirlemek için KDU yaklaşımlarına yönelik yapılacak güncel literatür araştırmaları, kapsamlı değerlendirmeler ve bilgi kaynakları önem taşımaktadır. Bu çalışma, Türkiye’deki fizyoterapi ve rehabilitasyon eğitiminde KDU yaklaşımının entegrasyonunu araştırarak öğrenme hedefleri için bir değerlendirme sunmayı amaçlamıştır.Öğe Investigation of graphene-coated Ag/AgCl electrode performance in surface electromyography measurement(Elsevier, 2022) Alcan, Veysel; Harputlu, Ersan; Ünlü, Cumhur Gökhan; Ocakoğlu, Kasım; Zinnuroğlu, MuratConventional silver-silver chloride (Ag/AgCl) electrodes are widely used for recording surface electromyography (sEMG) with a conductive gel. However, for long-term sEMG recording, the gel has some disadvantages that cause high impedance. Therefore, the dry electrodes have been alternatively purposed to overcome these disadvantages. Recently, the nanomaterial-based dry electrodes have been developed for long term electrophysiological signal recording. In the present study, we aimed to develop a graphene-coated Ag/AgCl electrode for long-term recording. We transferred single layer graphene (SLG) on the Ag/AgCl electrode surface by using chemical vapor deposition and confirmed this process by Raman scattering spectroscopy and scanning electron microscopy. We then compared the graphene-coated Ag/AgCl and conventional Ag/AgCl electrodes by evaluating median motor nerve conduction studies (mNCS) and their impedance. The charge transfer resistance (Rct) for the Ag/AgCl electrode (4170 ?) was much higher than graphene-coated Ag/AgCl electrode (Rct = 24.6 ?). For median mNCS measurements without gel, the graphene-coated Ag/AgCl electrode provided a better amplitude of distal and proximal compound muscle action potential (28.3 mV and 25.8 mV, respectively) than the Ag/AgCl electrode (21.8 mV and 20.9 mV, respectively). Consequently, the present study suggests promising results in terms of the usability of graphene-coated Ag/AgCl electrodes for long-term monitoring and wearable systems applications of sEMG. In future studies, we aim to investigate clinical applicability of graphene-coated sEMG electrodes that include extended clinical settings and larger study population.Öğe Karpal Tünel Sendromu Temelli Elektronik Sağlık Kayıt Sisteminin Geliştirilmesi(2019) Talan, Mehmet İbrahim; Canal, Mehmet Rahmi; Alcan, Veysel; Zınnuroglu, Murat; Akarkamçı Kaya, HilalKarpal tünel sendromunun (KTS) tanısında, fiziksel muayene, klinik testler ve elektrofizyolojik yöntemler kullanılmaktadır. Fakat pratikte uygulanan klinik ve elektrofizyolojik testlerde klinik ve laboratuvarlar için bir standart bulunmamaktadır. Bundan dolayı Elektronik Sağlık Kaydı (ESK) sistemlerinde, veri parçalanması veya uyumsuzluklar meydana gelebilmektedir. Ayrıca bu ESK sistemlerinde, ikincil kullanım ve farklı biyomedikal araştırma hedefleri dikkate alınmamakta ve rutin dökümantasyon işlemi sırasında, eksik, hatalı, tutarsız veri girişleri ve hatalı kodlamaları yapılabilmektedir. Bu çalışma ile, KTS tanısında farklı klinik ve merkezlerce de kullanılabilecek bir ESK sisteminin geliştirilmesi ve böylelikle standartlaştırılmış, kaliteli, öngörücü, önleyici, kişiselleştirilmiş ve gerçek zamanlı katılımcı bir KTS biyomedikal veri ambarının oluşturulması hedeflenmiştir. KTS tabanlı ESK sistemi, Microsoft Visual Studio C# programlama dili kullanılarak geliştirilmiştir. Ayrıca; yeni hasta kaydı esnasında KTS ön tanısı için WEKA programı kullanılarak veri madenciliği yöntemine dayalı bir klinik karar destek sistemi (KKDS) ile desteklenmiştir. Geliştirilen ESK sistemi, klinik ve elektrofizyoloijk test sonuçlarının yanısıra hassas tıp yaklaşımı çerçevesinde genetik ve çevresel varyantların da tek bir veri tabanına entegre edilmesine imkan tanımakta ve ikincil kullanım amacıyla geniş ölçekli doğru eksiksiz ve aynı standartta bir veri ambarı sunabilmektedir.Öğe New Optimized Deep Learning Application for COVID-19 Detection in Chest X-ray Images(Mdpi, 2022) Karim, Ahmad Mozaffer; Kaya, Hilal; Alcan, Veysel; Sen, Baha; Hadimlioglu, Ismail AlihanDue to false negative results of the real-time Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) test, the complemental practices such as computed tomography (CT) and X-ray in combination with RT-PCR are discussed to achieve a more accurate diagnosis of COVID-19 in clinical practice. Since radiology includes visual understanding as well as decision making under limited conditions such as uncertainty, urgency, patient burden, and hospital facilities, mistakes are inevitable. Therefore, there is an immediate requirement to carry out further investigation and develop new accurate detection and identification methods to provide automatically quantitative evaluation of COVID-19. In this paper, we propose a new computer-aided diagnosis application for COVID-19 detection using deep learning techniques. A new technique, which receives symmetric X-ray data as the input, is presented in this study by combining Convolutional Neural Networks (CNN) with Ant Lion Optimization Algorithm (ALO) and Multiclass Naive Bayes Classifier (NB). Moreover, several other classifiers such as Softmax, Support Vector Machines (SVM), K-Nearest Neighbors (KNN) and Decision Tree (DT) are combined with CNN. The promising results of these classifiers are evaluated and presented for accuracy, precision, and F1-score metrics. NB classifier with Ant Lion Optimization Algorithm and CNN produced the best results with 98.31% accuracy, 100% precision and 98.25% F1-score and with the lowest execution time.Öğe SAMPLE ENTROPY ANALYSIS OF HEART RATE VARIABILITY IN RR INTERVAL DETECTION(2020) Alcan, VeyselEntropy is a robust method that is able to measure irregularities or the generalbehavior of the complex time series which could be continuously interact with manydifferent and independent factors in time. This study aimed to investigate thesample entropy measurement of heart rate variability (HRV) for evaluating of 50Hzinterference and baseline wander (BW) noise effects on RR interval. Three differentsynthetic electrocardiogram (ECG) signals were recorded using the simulatordevice. Sample Entropy (SampEn) values of full length and windowed length of datawere calculated to track and identify RR intervals. It was found that adult normalsinus rhythm (NSR) signal without noise had the most regular and consistent resultswhile adult ECG signal with BW noisy had the most irregular and inconsistentresults. Furthermore, the BW noisy had more effect on irregularity ECG signal than50 Hz interference. Consequently, the SampEn provided the measurement ofirregularity and randomness of ECG data. However, it was found that thedetermination of RR intervals for classification and decision support systems wasnot practical in real-time analysis of HRV from raw ECG recordings because of noisyaffect.
