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    Application of Higuchi's Fractal Dimension for the Statistical Analysis of Human EEG Responses to Odors
    (Ieee, 2018) Seker, Mesut; Ozerdem, Mehmet Sirac
    The purpose of this study is to evaluate the fractal dimension (FD) analysis of pleasant-unpleasant odor EEGs. Higuchi's fractal dimension (HFD), which calculates FD directly in time domain, was preferred as a nonlinear signal analysis method. EEG recordings of 6 males were collected for dataset. Results showed that HFD values of pleasant and unpleasant odor EEGs were not in normal distribution and variances between independent variables were not homogeneous in all EEG channels. HFD values of pleasant odors were significantly different from unpleasant ones in O2 (right occipital) and T7 (left temporal) channels. There was a strong correlation between frontal lobes (F3-F4) for all class of odors. HFD values of unpleasant odors were higher than pleasant odors. It showed that unpleasant odor EEGs have more complex patterns than pleasant ones. The proposed work was performed with statistical tools.
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    Autoencoders Based Deep Learning Approach for Focal-Nonfocal EEG Classification Problem
    (Ieee, 2019) Seker, Mesut; Ozerdem, Mehmet Sirac
    EEG markers are the records of brain electrical activity which gives meaningful notice about individuals status. Detection of neurological diseases is only possible with effective analysis of EEG records. Epilepsy is a such neurological disease that has been a serious health problem affects life quality of human being. EEG based epilepsy detection in an effective and reliable way is a crucial issue for researchers. Effective feature extraction techniques to diminish input vector is a significant point in applications. In this study, auto-encoder based unsupervised feature extraction method was used and a deep learning approach was investigated to classify focal-non-focal EEG records. Proposed work has superiority in contrast to conventional methods because dataset was classified without using pre-processing and dimensionality-reduction methods. It has been thought that this work proposes an effective approach to diagnose epilepsy by using deep neural networks.
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    Classification of EEG Data Sets with Hilbert Transform
    (Ieee, 2016) Seker, Mesut; Özerdem, Mehmet Sirac
    Electroencephalographic (EEG) records which are related to the electrical activity of the brain are one of the most useful tools which are used in diagnosis of neurologic diseases. The aim of this study was to classify different sets of EEG signals by using Hilbert transform and artificial neural networks (ANN). The EEG data used in this study has been acquired from database of Epileptology Department of Bonn University. The database constitutes of five data sets, namely A, B, C, D and E. Besides, each data set has a difference due to healthy/ epileptic subject, eyes open/ closed, the position of electrode, seizure-free or seizure activity. A-B, A-E, C-D and A-B-E signal groups are classified with each other. For classification, magnitude and phase difference components obtained with Hilbert transform were used. To get the different frequency (theta (4-7Hz), alpha (8-13Hz), beta (12-38Hz), all (0.5-40Hz)) band, the signal filtered with band pass filter. The classification result of phase difference is higher than the amplitude based result. The highest performances of data sets are; 100% for A-B (phase difference, 0.5-40Hz, 7x30x2 network structure), 99.93% for A-E (phase difference, theta band, 7x75x2 network structure), 99.68% for C-D (phase difference, 0.540Hz, 7x30x2 network structure) and 97.72% for A-B-E (phase difference, theta, 7x20x3 network structure).
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    Classification of Mental Task EEG Records Using Hjorth Parameters
    (Ieee, 2017) Turk, Omer; Seker, Mesut; Akpolat, Veysi; Ozerdem, Mchmet Sirac
    The effects of mental activities on brain dynamics is the main field that studied for a long time, but the results of studies have not reached the desired level. The aim of present study was to classify the mental task EEG records by using Hjorth parameters. hi this study, EEG signals that recorded from 9 subjects were used. EEG signals were recorded by applying a experimental paradigm which contains five stimuli related to different mental task. These stimuli are defined as condition word mental subtraction spatial navigation right hand motor imagery and feet motor imagery Wavelet packet transform was used to obtain sub bands of EEC signals. Statistical parameters that consist of mobility, complexity and Mahalanobis distance were applied to sub-bands. Feature vectors were classified by using artificial neural network. When classification performances related to mental activities were examined, the best classification accuracy was obtained as nearly 80% for 'condition word - mental subtraction', ('spatial navigation feet motor imagery;' and 'spatial navigation - condition word'. The lowest classification accuracy was obtained for 'mental subtraction - right hand motor imagery,', 'condition word - right hand motor imagery' and 'spatial navigation right hand motor imagery'. The classification accuracies related to all stimuli that classifed among themselves were obtained as 77,61%.
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    The clinical and pathologic characteristics of 400 gastrointestinal stroinal tumor patients from Turkey: The final results of the Turkish Anatolian Society of Medical Oncology Multicenter Registery
    (Lippincott Williams & Wilkins, 2014) Sevinc, Alper; Seker, Mesut; Yildiz, Ramazan; Cihan, Sener; Kaplan, Mehmet Ali; Dane, Faysal; Karaca, Halit
    [Abstract Not Available]
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    Clinical and Pathologic Features of Patients with Rare Ovarian Tumors: Multi-Center Review of 167 Patients by the Anatolian Society of Medical Oncology
    (Asian Pacific Organization Cancer Prevention, 2013) Bilici, Ahmet; Inanc, Mevlude; Ulas, Arife; Akman, Tulay; Seker, Mesut; Babacan, Nalan Akgul; Inal, Ali
    Background: Non-epithelial malignant ovarian tumors and clear cell carcinomas, Brenner tumors, transitional cell tumors, and carcinoid tumors of the ovary are rare ovarian tumors (ROTs). In this study, our aim was to determine the clinicopathological features of ROT patients and prognostic factors associated with survival. Materials and Methods: A total of 167 patients with ROT who underwent initial surgery were retrospectively analyzed. Prognostic factors that may influence the survival of patients were evaluated by univariate and multivariate analyses. Results: Of 167 patients, 75 (44.9%) were diagnosed with germ-cell tumors (GCT) and 68 (40.7%) with sex cord-stromal tumors (SCST); the remaining 24 had other rare ovarian histologies. Significant differences were found between ROT groups with respect to age at diagnosis, tumor localization, initial surgery type, tumor size, tumor grade, and FIGO stage. Three-year progression-free survival (PFS) rates and median PFS intervals for patients with other ROT were worse than those of patients with GCT and SCST (41.8% vs 79.6% vs 77.1% and 30.2 vs 72 vs 150 months, respectively; p=0.01). Moreover, the 3-year overall survival (OS) rates and median OS times for patients with both GCT and SCST were better as compared to patients with other ROT, but these differences were not statistically significant (87.7% vs 88.8% vs 73.9% and 170 vs 122 vs 91 months, respectively; p=0.20). In the univariate analysis, tumor localization (p<0.001), FIGO stage (p<0.001), and tumor grade (p=0.04) were significant prognostic factors for PFS. For OS, the univariate analysis indicated that tumor localization (p=0.01), FIGO stage (p=0.001), and recurrence (p<0.001) were important prognostic indicators. Multivariate analysis showed that FIGO stage for PFS (p=0.001, HR: 0.11) and the presence of recurrence (p=0.02, HR: 0.54) for OS were independent prognostic factors. Conclusions: ROTs should be evaluated separately from epithelial ovarian cancers because of their different biological features and natural history. Due to the rarity of these tumors, determination of relevant prognostic factors as a group may help as a guide for more appropriate adjuvant or recurrent therapies for ROTs.
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    Multicentric study on malignant pleural mesothelioma in Turkey: clinicopathologic and survival characteristics of 282 patients
    (Humana Press Inc, 2012) Elkiran, Emin Tamer; Kaplan, Mehmet Ali; Sevinc, Alper; Aksoy, Sercan; Demirci, Umut; Seker, Mesut; Harputluoglu, Hakan
    Malignant pleural mesothelioma (MPM) is a relatively rare, but aggressive tumor that causes high mortality. The major risk factor involved in the etiology is environmental and occupational exposure to asbestos. The optimal modality of therapy is controversial. The present study retrospectively evaluated the data pertinent to 282 patients who were examined and treated in 11 different medical oncology centers in Turkey. There were 161 males (57.1 %) and 121 females (42.9 %), with a mean age of 56.38 +/- A 12.07 years. Surgery was used in 74 patients, 21 patients (28.4 %) received only chemotherapy and 28 patients (37.8 %) received chemoradiotherapy after surgery. The median survival in patients who were administered adjuvant therapy after surgery was 24 months, while the median survival in patients who had only surgery was 6 months (p = 0.029). 106 patients were administered pemetrexed-platinum combination and 35 patients were administered gemcitabine-platinum combination as front-line chemotherapy. Median survival, 1- and 2-year survival rates in patients who received platinum analogues and pemetrexed or gemcitabine combinations were found statistically similar (p = 0.15). The median survival for all patients with MPM in our study was 18 months. The main factors influencing the overall survival were stage of the disease (p = 0.020), performance status (p < 0.001), asbestos exposure (p = 0.030) and mesothelioma histological subtypes (p < 0.001). Results of our study suggest that multi-modality treatment regimens consisting of surgery, radiotherapy and chemotherapy prolong overall survival. Survival rates in patients who received combining platinum analogues with pemetrexed or gemcitabine as front-line chemotherapy were found similar.
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    Prognostic Factors in Gastrointestinal Stromal Tumors: Multicenter Experience of 333 Cases from Turkey
    (H G E Update Medical Publishing S A, 2013) Seker, Mesut; Sevinc, Alper; Yildiz, Ramazan; Cihan, Sener; Kaplan, Mehmet Ali; Gokdurnali, Ayse; Dane, Faysal
    Background/Aims: Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal neoplasm of the gastrointestinal tract. In an attempt to survey the approximate incidence, clinicopathological characteristics, and immunophenotypic features of GISTs in Turkey, we conducted a clinicopathological and immunohistochemical analysis of GISTs. Methodology: Three hundred and thirty-three patients with GIST from nine institutions in Turkey were retrospectively evaluated. Results: Between January 2001 and March 2011, a total of 333 patients with GISTs were included; of these, 204 (61.2%) were male and 129 (38.8%) were female. The median age was 55 years (range; 22402 years). At the median follow-up of 26 months (range; 4-166 months), the 1-, 3- and 5-year OS rates of the 333 patients were 96.9%, 85.8% and 78.5%, respectively. The 5-year DFS rate was 40%. The 5-year OS rate and median OS time for the patients with R-0 resection were significantly higher than for patients with metastatic diseases (79.7 vs. 75.7% and not reached vs. 115 months, respectively, p=0.04). Conclusion: Although our results should be confirmed by prospective studies, we believe that they contribute to the literature because the study included both resectable and metastatic or unresectable GIST patients and multicenter findings from Turkey.
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    Spectrum Estimation of Odor EEG Responses with Parametric-Nonparametric Spectral Analysis Methods
    (Ieee, 2018) Seker, Mesut; Akin, Mehmet; Ozerdem, Mehmet Sirac
    It is known that external stimulus such as visual, auditory and odor have effect on brain activity. Effects of odor stimuli, which has complex structure, on central nerveous system is lack of knowledge in literature. The goal of proposed study is to show how pleasant-unpleasant odors effect brain waves by using spectral analysis methods and discriminating different odors through statistical methods and a classifier. The EEG dataset used in study was taken from 6 participants while their eyes are closed and 4 odor (2 pleasant-2unpleasant) stimulus were applied to them using 14 chanelled EMOTIV-EPOC headset. Discrete Wavelet Transform (DWT) was used to pre-processed signals obtained from embedded filters to extract more meaningful EEG sub-bands (delta-tetha-alpha-beta). First of all, power spectrum graphics of these sub-bands was drawn using Welch's method to see how pleasant-unpleasant odor EEGs behave. Then, spectrum coefficients were gained by help of parametric (Burg, Yule-Walker, Covariance, Modified Covariance) and non-parametric (Welch's) methods. Selected feature vectors from these coefficients were classified. Selected features are min, max value and standard deviation. k-NN was chosen for classification algorithm. Avarage power spectrum analysis showed that unpleasant odor EEG has higher values than pleasant one with respect to all sub-bands. Parametric methods gave better results to discriminate odor EEGs. Burg method has highest classification rate among others.
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    Treatment modalities in primary gastric lymphoma: the effect of rituximab and surgical treatment. A study by the Anatolian Society of Medical Oncology
    (Termedia Publishing House Ltd, 2014) Mehmet, Kucukoner; Sener, Cihan; Uyeturk, Ummugul; Seker, Mesut; Tastekin, Didem; Tonyali, Onder; Balakan, Ozan
    Aim of the study: Gastrointestinal lymphoma is the most common type of extranodal lymphoma and commonly involved site is the stomach. We have compared the superiority between treatment modalities for primary gastric lymphoma and we want to investigate efficacy of rituximab in gastric lymphoma. Material and methods: Between April 2002 and December 2011, 146 patients with a histologically confirmed primary gastric lymphoma, initially diagnosed at eight different Cancer Centers within Turkey were evaluated retrospectively. According to the treatment modality, the patients were divided into chemotherapy (CT) alone, chemotherapy and radiotherapy (CRT), surgery and chemotherapy (SCT), surgery along with chemotherapy and radiotherapy (SCRT), and surgery (S) alone groups. Results: Median follow-up period was 25.5 months. The 5-year EFS (event free survival) and OS (overall survival) rates for the patients were 55% and 62.3% respectively. In Log rank analysis of OS and EFS, we have identified levels of albumin and hemoglobine, IPI score, stage at diagnosis as factors influencing survival. In multivariate analysis of OS and EFS, only albumin and stage at diagnosis were factors independently contributing to survival. There was no statistically significant difference in terms of survival between different treatment modalities (p = 0.707 in EFS and p = = 0.124 in OS). In analysis of patients treated with chemotherapy alone, there was no a statistically significant difference in terms of EFS and OS between chemotherapy regimens with or without rituximab in localized and advanced stage groups (p = 0.264 and p = 0.639). There was no statistical difference in survival rate (EFS and OS) between surgical or non-surgical treatment modalities for localized/ advanced stage gastric lymphoma groups (p = 0.519 / p = 0.165). Conclusions: There are several treatment options due to similar results in different treatment modalities. Also benefit of rituximab treatment in gastric lymphoma is still a controversial subject. Additional prospective trials are definitely required in order to clarify use of rituximab in treatment of extranodal gastric lymphoma.