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Publication Metadata only Fluorine determination in human and animal bones by particle-induced gamma-ray emission(Springer Verlag, 2001) Sastri, Chaturvedula S.; Lyengar, Venkatesh; Blondiaux, Gilbert B.; Tessier, Yves; Petri, Hermann; Hoffmann, Peter S.; Aras, Namik K.; Zaichick, Vladimir Ye; Ortner, Hugo Manfred; Sastri, Chaturvedula S., Fachbereich Material- und Geowissenschaften, Technische Universität Darmstadt, Darmstadt, Germany; Lyengar, Venkatesh, International Atomic Energy Agency, Vienna, Vienna, Austria; Blondiaux, Gilbert B., Centre de Recherches Internationales Sciences Po, Paris, France; Tessier, Yves, Centre de Recherches Internationales Sciences Po, Paris, France; Petri, Hermann, Forschungszentrum Jülich GmbH, Julich, Germany; Hoffmann, Peter S., Fachbereich Material- und Geowissenschaften, Technische Universität Darmstadt, Darmstadt, Germany; Aras, Namik K., Department of Chemistry, Middle East Technical University (METU), Ankara, Turkey, Bahçeşehir Üniversitesi, Istanbul, Turkey; Zaichick, Vladimir Ye, A. Tsyb Medical Radiological Research Center, Obninsk, Russian Federation; Ortner, Hugo Manfred, Fachbereich Material- und Geowissenschaften, Technische Universität Darmstadt, Darmstadt, GermanyFluorine was determined in the iliac crest bones of patients and in ribs collected from post-mortem investigations by particle-induced gamma-ray emission based on the 19F(p,p′y)19F reaction, using 2.0/2.5 MeV protons. The results indicate that for 68% of the human samples the F concentration is in the range 500-1999 μg g-1. For comparison purposes fluorine was also determined in some animal bones, in some animal tissues lateral profiles of fluorine were measured. © Springer-Verlag 2001. © 2020 Elsevier B.V., All rights reserved.Publication Metadata only Relationship between general and context-specific attachment orientations in a Turkish sample(2006) Imamoǧlu, Selen; Olcay Imamoĝlu, E.; Imamoǧlu, Selen, Faculty of Communication, Bahçeşehir Üniversitesi, Istanbul, Turkey; Olcay Imamoĝlu, E., Department of Psychology, Middle East Technical University (METU), Ankara, TurkeyThe authors explored the relationship between general and context-specific attachment orientations involving family, peer, and romantic contexts. Participants were 110 Turkish university students (50 men, 60 women). The authors used the Turkish form of K. Bartholomew and L. M. Horowitz's (1991) Relationship Questionnaire (RQ) to measure participants' general and specific attachment orientations. Using 5-point Likert-type scales, participants specified the degree to which each of the 4 descriptions of RQ (i.e., of secure, preoccupied, dismissing, and fearful orientations) represented (a) how they generally felt in close relationships, and then how they felt in their (b) family relationships, (c) romantic relationships, and (d) peer relationships. The present results indicated that participants who were generally high rather than low on a particular attachment orientation tended to be so across the 3 contexts, thereby supporting the trait-like conceptualization of attachment styles. However, the present results also supported conceptualization of attachment orientations as specific context-related tendencies because regardless of their general orientations, participants reported feeling relatively more secure in some relationships (e.g., family) than in others (e.g., romantic). The authors discussed the present results as supporting (a) the coexistence of both general and specific attachment orientations in the cognitive system and (b) the cross-cultural validity of attachment orientations. Copyright © 2006 Heldref Publications. © 2009 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Prediction of cyclosporine A blood levels: An application of the adaptive-network-based fuzzy inference system (ANFIS) in assisting drug therapy(2008) Gören, Sezer; Karahoca, Adem; Onat, Filiz Yilmaz; Gören, Mehmet Zafer; Gören, Sezer, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Karahoca, Adem, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Onat, Filiz Yilmaz, Department of Pharmacology and Clinical Pharmacology, Marmara Üniversitesi Tip Fakültesi, Istanbul, Turkey; Gören, Mehmet Zafer, Department of Pharmacology and Clinical Pharmacology, Marmara Üniversitesi Tip Fakültesi, Istanbul, TurkeyObjective: Therapeutic drug monitoring (TDM) is a procedure in which the levels of drugs are assayed in various body fluids with the aim of individualizing the dose of critical drugs, such as cyclosporine A. Cyclosporine A assays are performed in blood. Methods: We proposed the use of the Takagi and Sugeno-type adaptive-network-based fuzzy inference system (ANFIS) to predict the concentration of cyclosporine A in blood samples taken from renal transplantation patients. We implemented the ANFIS model using TDM data collected from 138 patients and 20 input parameters. Input parameters for the model consisted of concurrent use of drugs, blood levels, sampling time, age, gender, and dosing intervals. Results: Fuzzy modeling produced eight rules. The developed ANFIS model exhibited a root mean square error (RMSE) of 0.045 with respect to the training data and an error of 0.057 with respect to the checking data in the MATLAB environment. Conclusion: ANFIS can effectively assist physicians in choosing best therapeutic drug dose in the clinical setting. © 2008 Springer-Verlag. © 2009 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Organizational commitment of military physicians(Association of Military Surgeons of the US pubsvc.tsp@sheridan.com, 2009) Demir, Cesim; Şahin, Bayram; Tekef, Kadir; Uçar, Muharrem; Kursun, Olcay; Demir, Cesim, Gülhane Eğitim ve Araştırma Hastanesi, Ankara, Turkey; Şahin, Bayram, Department of Health Care Management, Hacettepe Üniversitesi, Ankara, Turkey; Tekef, Kadir, Gülhane Eğitim ve Araştırma Hastanesi, Ankara, Turkey; Uçar, Muharrem, Department of Medical History and Deontology, Gülhane Eğitim ve Araştırma Hastanesi, Ankara, Turkey; Kursun, Olcay, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyAn individual's loyalty or bond to his or her employing organization, referred to as organizational commitment, influences various organizational outcomes such as employee motivation, job satisfaction, performance, accomplishment of organizational goals, employee turnover, and absenteeism. Therefore, as in other sectors, employee commitment is crucial also in the healthcare market. This study investigates the effects of organizational factors and personal characteristics on organizational commitment of military physicians using structural equation modeling (SEM) on a self-report, cross-sectional survey that consisted of 635 physicians working in the 2 biggest military hospitals in Turkey. The results of this study indicate that professional commitment and organizational incentives contribute positively to organizational commitment, whereas conflict with organizational goals makes a significantly negative contribution to it. These results might help develop strategies to increase employee commitment, especially in healthcare organizations, because jobrelated factors have been found to possess greater impact on organizational commitment than personal characteristics. Reprint and Copyright © by Association of Military Surgeons of U.S., 2009. © 2017 Elsevier B.V., All rights reserved.Publication Metadata only Information system design for a hospital emergency department: A usability analysis of software prototypes(2010) Karahoca, Adem; Bayraktar, Erkan; Tatoglu, Ekrem; Karahoca, Dilek Yiğit; Karahoca, Adem, Faculty of Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Bayraktar, Erkan, Faculty of Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Tatoglu, Ekrem, Faculty of Economics and Administrative Sciences, Bahçeşehir Üniversitesi, Istanbul, Turkey; Karahoca, Dilek Yiğit, Faculty of Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyStudy objective: The purpose of this study is to evaluate the usability of emergency department (ED) software prototypes developed for Tablet personal computers (Tablet PCs) in order to keep electronic health records (EHRs) of patients errorless and accessible through mobile technologies. In order to serve this purpose, two alternative prototypes were developed for Tablet PCs: Mobile Emergency Department Software (MEDS) and Mobile Emergency Department Software Iconic (MEDSI) among which the user might choose the more appropriate one for ED operations based on a usability analysis involving the target users. Methods: The study is based on a case study of 32 potential users of our prototypes at the ED of Kadikoy-AHG in Istanbul, Turkey. We examined usability of the prototypes for medical information systems by means of Nielsen's heuristic evaluation and cognitive walkthrough methods relying on 7-point scales, and scenario completion success rate and average scenario completion time, respectively. Results: The implementation of MEDSI in our case study confirmed the view that the usability evaluation results of iconic GUIs were better than those of non-iconic GUIs in terms of Nielsen's heuristic evaluation, effectiveness and user satisfaction. For the whole sample, paired t-test scores indicated that there was a significant difference (p < 0.01) between mean values of Nielsen's usability scores toward MEDS and MEDSI indicating that MEDSI was evaluated more favorably than MEDS. As for effectiveness of the prototypes, significant differences (p < 0.01) were noted between MEDS and MEDSI in terms of both overall scenario completion success rate and average scenario completion time. Similarly, for the full sample of users independent sample t-test scores indicated that MEDSI was perceived significantly more favorable (p < 0.01) than MEDS in terms of overall user satisfaction. Conclusion: The study provides two important contributions to the extant literature. First, it addresses a topic and methodology that serves potentially interesting to the biomedical informatics community. Drawing on good background information and appropriate context, it involves various aspects of usability testing. Another contribution of the study lies in its examination of two different prototypes during the design phase involving the target users. © 2009 Elsevier Inc. All rights reserved. © 2010 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Classification of the colonic polyps in CT-colonography using region covariance as descriptor features of suspicious regions(2010) Kılıç, Niyazi; Kursun, Olcay; Uçan, Osman Nuri; Kılıç, Niyazi, Department of Electrical and Electronics Engineering, Istanbul Üniversitesi, Istanbul, Turkey; Kursun, Olcay, Department of Electrical and Electronics Engineering, Istanbul Üniversitesi, Istanbul, Turkey; Uçan, Osman Nuri, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe present an algorithm to classify polyps in CT colonography images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, they cannot simply be fed to traditional machine learning tools such as support vector machines (SVMs) or artificial neural networks (ANNs). To benefit from the simple yet one of the most powerful nonparametric machine learning approach k-nearest neighbor classifier, it suffices to compute the pairwise distances among the covariance descriptors using a distance metric involving their generalized eigenvalues, which also follows from the Lie group structure of positive definite matrices. This approach is fast and discriminates polyps from non-polyps with high accuracy using only a small size descriptor, which consists of 36 unique features per image region extracted from the suspicious regions that we have obtained by combined cellular neural network (CNN) and template matching detection method. These suspicious regions are, in average, 15 × 17 = 255 pixels in our experiments. © Springer Science + Business Media, LLC 2008. © 2010 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Telediagnosis of parkinson's disease using measurements of dysphonia(2010) Sakar, C. Okan; Kursun, Olcay; Sakar, C. Okan, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kursun, Olcay, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyParkinson's disease (PD) is a neurological illness which impairs motor skills, speech, and other functions such as mood, behavior, thinking, and sensation. It causes vocal impairment for approximately 90% of the patients. As the symptoms of PD occur gradually and mostly targeting the elderly people for whom physical visits to the clinic are inconvenient and costly, telemonitoring of the disease using measurements of dysphonia (vocal features) has a vital role in its early diagnosis. Such dysphonia features extracted from the voice come in variety and most of them are interrelated. The purpose of this study is twofold: (1) to select a minimal subset of features with maximal joint relevance to the PD-score, a binary score indicating whether or not the sample belongs to a person with PD, and (2) to build a predictive model with minimal bias (i.e. to maximize the generalization of the predictions so as to perform well with unseen test examples). For these tasks, we apply the mutual information measure with the permutation test for assessing the relevance and the statistical significance of the relations between the features and the PD-score, rank the features according to the maximum-relevance-minimum-redundancy (mRMR) criterion, use a Support Vector Machine (SVM) for building a classification model and test it with a more suitable cross-validation scheme that we called leave-one-individual-out that fits with the dataset in hand better than the conventional bootstrapping or leave-one-out validation methods. © 2009 Springer Science+Business Media, LLC. © 2010 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Whole-exome sequencing identifies recessive WDR62 mutations in severe brain malformations(2010) Bilgüvar, Kaya; Öztürk, Ali Kemal; Louvi, Angeliki; Kwan, Kenneth Y.; Choi, Murim; Tatlí, Burak; Yalnizoǧlu, Dilek; Tüysüz, Beyhan; Caglayan, Ahmet Okay; Gökben, Sarenur; Bilgüvar, Kaya, Department of Neurosurgery, Yale School of Medicine, New Haven, United States, Department of Neurobiology, Yale School of Medicine, New Haven, United States, Department of Genetics, Yale School of Medicine, New Haven, United States; Öztürk, Ali Kemal, Department of Neurosurgery, Yale School of Medicine, New Haven, United States, Department of Neurobiology, Yale School of Medicine, New Haven, United States, Department of Genetics, Yale School of Medicine, New Haven, United States; Louvi, Angeliki, Department of Neurosurgery, Yale School of Medicine, New Haven, United States, Department of Neurobiology, Yale School of Medicine, New Haven, United States, Department of Genetics, Yale School of Medicine, New Haven, United States; Kwan, Kenneth Y., Department of Neurobiology, Yale School of Medicine, New Haven, United States, Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, United States; Choi, Murim, Department of Genetics, Yale School of Medicine, New Haven, United States; Tatlí, Burak, Department of Pediatrics, İstanbul Tıp Fakültesi, Istanbul, Turkey; Yalnizoǧlu, Dilek, Department of Pediatrics, Hacettepe Üniversitesi, Ankara, Turkey; Tüysüz, Beyhan, Department of Pediatrics, İstanbul University-Cerrahpaşa Cerrahpaşa Faculty of Medicine, Istanbul, Turkey; Caglayan, Ahmet Okay,; Gökben, Sarenur, Department of Pediatrics, Ege University Medical School, Izmir, TurkeyThe development of the human cerebral cortex is an orchestrated process involving the generation of neural progenitors in the periventricular germinal zones, cell proliferation characterized by symmetric and asymmetric mitoses, followed by migration of post-mitotic neurons to their final destinations in six highly ordered, functionally specialized layers1,2. An understanding of the molecular mechanisms guiding these intricate processes is in its infancy, substantially driven by the discovery of rare mutations that cause malformations of cortical development3-6. Mapping of disease loci in putative Mendelian forms of malformations of cortical development has been hindered by marked locus heterogeneity, small kindred sizes and diagnostic classifications that may not reflect molecular pathogenesis. Here we demonstrate the use of whole-exome sequencing to overcome these obstacles by identifying recessive mutations in WD repeat domain 62 (WDR62) as the cause of a wide spectrum of severe cerebral cortical malformations including microcephaly, pachygyria with cortical thickening as well as hypoplasia of the corpus callosum. Some patients with mutations in WDR62 had evidence of additional abnormalities including lissencephaly, schizencephaly, polymicrogyria and, in one instance, cerebellar hypoplasia, all traits traditionally regarded as distinct entities. In mice and humans, WDR62 transcripts and protein are enriched in neural progenitors within the ventricular and subventricular zones. Expression of WDR62 in the neocortex is transient, spanning the period of embryonic neurogenesis. Unlike other known microcephaly genes, WDR62 does not apparently associate with centrosomes and is predominantly nuclear in localization. These findings unify previously disparate aspects of cerebral cortical development and highlight the use of whole-exome sequencing to identify disease loci in settings in which traditional methods have proved challenging. © 2010 Macmillan Publishers Limited. All rights reserved. © 2012 Elsevier B.V., All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Publication Metadata only Coupled nonparametric shape and moment-based intershape pose priors for multiple basal ganglia structure segmentation(2010) Uzunbaş, Mustafa Gökhan; Soldea, Octavian; Ünay, Devrim; Çetin, Müjdat; Unal, Gozde Bozkurt; Erçil, Aytül; Ekin, Ahmet; Uzunbaş, Mustafa Gökhan, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey, Department of Computer Science, Piscataway, United States; Soldea, Octavian, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Ünay, Devrim, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Çetin, Müjdat, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Unal, Gozde Bozkurt, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Erçil, Aytül, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Ekin, Ahmet, Video Processing and Analysis Group, Philips Research, Eindhoven, NetherlandsThis paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and intershape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance images. We present a set of 2-D and 3-D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy. © 2010 IEEE. © 2010 Elsevier B.V., All rights reserved.Publication Metadata only Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform(2010) Serbes, Görkem; Aydın, Nizamettin; Serbes, Görkem, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, TurkeyEarly and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB). © 2010 IEEE. © 2011 Elsevier B.V., All rights reserved.