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Objective: Epidural analgesia (EA) has positive effects on anesthetic requirement, blood loss, postoperative analgesia, and pulmonary function tests (PFTs). The purpose of the present study was to investigate the effect of EA on postoperative PFTs in liver transplant donors (LTDs)., Methods: In the present study, 66 LTDs were classified as total intravenous anesthesia (TIVA) and TIVA+EA groups. Patient's age, sex, body mass index, induction and maintenance dose of propofol (IDP and MDP), operation duration, forced expiratory volume in 1 second (FEV 1 ), forced vital capacity (FVC), FEV 1 /FVC ratio, visual analog scale (VAS), atelectasis scores, and lengths of intensive care unit (ICU) and hospital stays were recorded., Results: In the TIVA+EA group, IPD, MPD, delta-FEV 1 delta-FVC, VAS for all time, atelectasis score and length of hospital stay were significantly lower than in the TIVA group (P < .001 for all). Whereas VAS at the end of the operation was negatively correlated with delta-FEV 1 and delta-FVC (r 2 = 0.26 P < .001; r 2 = 0.41 P < .001; respectively), it was positively correlated with atelectasis score and length of ICU stay (r 2  = 0.49, P < .001; and r 2  = 0.41, P < .001; respectively). Atelectasis score was positively correlated with length of ICU stay (r 2  = 0.86, P < .001)., Conclusions: Reduced anesthetic requirement, better postoperative analgesia, reduced atelectasis score, and preserved PFTs can be provided with the use of EA in LTDs. Positive effects of EA on anesthesia requirement, pain management and pulmonary function are associated with outcomes., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Magnesium is an N-methyl-d-aspartate receptor blocker and is known to have analgesic effect. Hypomagnesemia can often be seen in liver transplantation and may be associated with higher morbidity and mortality. The objective of this study was to investigate the effects of intraoperative magnesium sulfate administration on postoperative tramadol requirement in liver transplant patients., Methods: Liver transplant patients >18 years of age were screened prospectively from October 2014 to April 2015. Of these, 35 randomly selected patients with normal blood magnesium level (≥1.8 mmol/L) were included in a control group and another 35 randomly selected patients with low magnesium level (<1.8 mmol/L) were given 50 mg/kg intravenous magnesium sulfate replacement in the last 30 minutes of the operation. All patients received standard anesthesia induction and maintenance. Patient's age, sex, body mass index, Model for End-Stage Liver Disease and Acute Physiology and Chronic Health Evaluation II scores, 24-hour tramadol requirement, mechanical ventilation duration, and time of 1st tramadol need were recorded., Results: In the magnesium group, mean 24-hour total tramadol requirement (3.7 mg/kg/d) and duration of mechanical ventilation (6.3 h) were significantly lower and time of 1st tramadol need (17.5 h) was significantly higher than in the control group (P < .001 for each). In the multivariate analysis, duration of mechanical ventilation was decreased by the usage of magnesium sulfate (P < .001)., Conclusions: Intraoperative use of magnesium sulfate in liver transplantation reduces the need for postoperative tramadol and duration of mechanical ventilation and therefore it is a candidate to be adjuvant agent., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: In Turkey, according to the directions of National Organ and Tissue Transplant Coordination System, a system has been established since 2008 of urgency priority for kidney transplantation in cases with imminent lack of access for either hemodialysis or peritoneal dialysis. In this study, we compared patient and graft outcomes between patients on the national waiting list having urgency priority for kidney transplantation (UKT) and those having the other kidney from the same deceased donor (control group)., Methods: We examined retrospective data of patients, who underwent transplantation under urgency priority allocation in Turkey from 2010 to 2014 and compared that group with other patients receiving kidney transplants from the same deceased donors (control group). Then we compared these patients for early and long-term patient and graft outcomes., Results: Forty-seven patients had UKT, and 40 patients received transplants from the same deceased donors. Mean follow-up of patients after transplantation was 18 ± 12 months. Eight patients with UKT and 4 patients in the control group lost their grafts. At follow-up, 7 patients died in the UKT group, and 4 patients died in the control group. Patient survival in the UKT group was 90% at 1 year and 83% at 2 years, and in the control group was 93% at 1 year and 84% at 2 years (P = .384). Graft survival was 87% at 1 year and 81% at 2 years in UKT, and 91% at both 1 and 2 years in the control group (P = .260)., Conclusions: Although patients with UKT showed lower graft and patient survivals than the control group, the difference was statistically nonsignificant. UKT can be an obligatory treatment model for patients with lack of vascular or peritoneal access for dialysis., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: To evaluate the influence of delivery mode on oxidative stress in human breast milk., Methods: Thirty-three women who delivered by vaginal birth and 55 women who underwent cesarean section (CS) were included in this study. Colostral samples were collected on the second day after delivery. Total antioxidative status (TAS), total oxidative status (TOS), oxidative stress index (OSI), malonyldialdehyde (MDA), and glutathione peroxidase (GSH-Px) levels were determined and compared., Results: Colostrum TAS was significantly higher in women of vaginal birth, than in women with CS (p < 0.001). Milk TOS and OSI were found to be significantly increased in women with CS under general anesthesia. A marked increase in colostral GSH-Px levels after vaginal delivery was also noticed (p < 0.001)., Conclusion: This study revealed that vaginal birth is associated with decreased oxidative stress in colostrum than CS, which suggest that mode of delivery plays an important role in the antioxidative production of breast milk.

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

Objectives: This study aims to investigate whether the time from the onset of symptoms to the start of treatment is a prognostic indicator in patients with idiopathic sudden sensorineural hearing loss (ISSNHL)., Patients and Methods: In this study, 96 patients (58 males, 38 females; mean age 37.8±2.5 years; range 16 to 67 years) who were diagnosed with ISSNHL in our clinic between January 1992 and April 2010 were retrospectively analyzed. All patients were treated with dextran 40 (rheomacrodex), pentoxifyllin, vitamin B complex and vitamin C regimen over 10 days with hospitalization and bed rest. The patients were tested by pure-tone audiometry. Audiograms were obtained on alternate days and at the end of the treatment., Results: There was a complete recovery in 45 (60%) of 75 patients whose treatment was started in the first seven days, while a partial recovery was observed in 17 (22.66%) and no recovery was observed in 13 (17.33%). There was a complete recovery in two (9.52%) of 21 patients whose treatment was started after the eighth day, while a partial recovery was observed in seven (33.33%) and no recovery was observed in 12 (57.14%)., Conclusion: Our study results suggest that treatment outcomes are better in the patients presenting to hospital at an early stage of loss of hearing.

This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

In this paper, an innovative data pre-processing method to improve the classification performance and to determine automatically the vertebral column disorders including disk hernia (DH), spondylolisthesis (SL) and normal (NO) groups has been proposed. In the classification of vertebral column disorders' dataset with three classes, a pairwise fuzzy C-means (FCM) based feature weighting method has been proposed. In this method, first of all, the vertebral column dataset has been grouped as pairwise (DH-SL, DH-NO, and SL-NO) and then these pairwise groups have been weighted using a FCM based feature set. These weighted groups have been classified using classifier algorithms including multilayer perceptron (MLP), k-nearest neighbor (k-NN), Naive Bayes, and support vector machine (SVM). The general classification performance has been obtained by averaging of classification accuracies obtained from pairwise classifier algorithms. To evaluate the performance of the proposed method, the classification accuracy, sensitivity, specificity, ROC curves, and f-measure have been used. Without the proposed feature weighting, the obtained f-measure values were 0.7738 for MLP classifier, 0.7021 for k-NN, 0.7263 for Naive Bayes, and 0.7298 for SVM classifier algorithms in the classification of vertebral column disorders' dataset with three classes. With the pairwise fuzzy C-means based feature weighting method, the obtained f-measure values were 0.9509 for MLP, 0.9313 for k-NN, 0.9603 for Naive Bayes, and 0.9468 for SVM classifier algorithms. The experimental results demonstrated that the proposed pairwise fuzzy C-means based feature weighting method is robust and effective in the classification of vertebral column disorders' dataset. In the future, this method could be used confidently for medical datasets with more classes., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Objectives: This study aims to evaluate the alterations in distances to the surgical margins on sheep tongue specimens, through resection, formalin fixation, frozen section, and microscopic examination., Materials and Methods: Fifty fresh sheep tongues were used in the study. A metal plate was fixed on the lateral aspect of each tongue to represent tumor tissues. A total of 40 specimens with either 1 cm or 2 cm distances as surgical safety margins of the surrounding plate were prepared using either scalpel or monopolar cautery (10 specimens were prepared for each group). Additional 10 specimens with 1 cm safety margins were prepared using either scalpel or monopolar cautery (5 specimens per group) for frozen section examination. Distances to the metal plates before resection were compared with the ones which were determined after resection, frozen section examination, 24-hour formalin fixation and microscopic examination., Results: Distances to the surgical margins were found to be decreased in all specimens after resection, 10% formalin fixation and microscopic examination. The distances to the surgical margins were observed to be reduced by 6.5-7.5% on average after resection, 10-12% on average after formalin fixation and 30% on average after microscopic examination, compared to the baseline values. The level of shrinkage was reduced by 6.3-10% following microscopic section preparation during frozen section examination., Conclusion: Seven to eight-millimeter distance to the surgical margin at minimum should be maintained to achieve a 5 mm in height surgical safety margin during sheep tongue resection. The distance defined by the pathologist may be multiplied with 1.42 to estimate around in-situ distance to the surgical margins. Therefore, 1.42 may be used as a corrective factor for sheep tongue tissues.

Familial Mediterranean fever (FMF) is a common and well-understood hereditary periodic fever syndrome. Hereditary periodic fever syndromes include a group of multisystem diseases characterized by recurrent fever attacks with inflammation affecting skin, joints, and some other tissues. These are FMF, tumor necrosis factor receptor, tumor necrosis factor receptor associated periodic syndrome, hyperimmunglobulinemia D syndrome, Muckle-Wells syndrome, and familial cold urticaria. In literature, it is determined that some of these diseases cause hearing loss. In light of the foregoing, we thought that FMF patients may have the same type of subclinical hearing loss and, therefore, the hearing ability of these patients was evaluated with otoacoustic emission and high frequency audiometry tests.

Chronic otitis media (COM) is defined as persistent infection or inflammation of the middle ear and mastoid air cells. The proximity of the middle ear cleft and mastoid air cells to the intratemporal and intracranial compartments places structures located in these areas at increased risk of infectious complications. The complications of COM are divided into intracranial and extracranial complications. The development and appropriate use of antibiotics have led to a decrease in these potentially devastating complications. However, they continue to occur, and clinical vigilance is required for early detection and treatment. We reported a case with multiple complications, both intracranial and extracranial secondary to COM.

Juvenile nasopharyngeal angiofibromas are locally growing and highly vascular tumors. They are primarily treated through surgical excision ranging from an open approach to an endoscopic approach. We presented a 20-year-old man with a giant juvenile nasopharyngeal angiofibroma that bilaterally obliterated the pterygopalatine fossa, invaded the sphenoid bone, and extended to the left nasal passage. His complaints were epistaxis and nasal obstruction. After embolization, the patient was treated surgically using the endoscopic approach and declared cured and discharged without any complications.

A novel highly sensitive electrochemical carboxymethylcellulose-gelatin-TiO(2)-superoxide dismutase biosensor for the determination of O(2)(•-) was developed. The biosensor exhibits high analytical performance with a wide linear range (1.5 nM to 2 mM), low detection limit (1.5 nM), high sensitivity and low response time (1.8s). The electron transfer of superoxide dismutase was first accomplished at the carboxymethylcellulose-gelatin-Pt and carboxymethylcellulose-gelatin-TiO(2)-Pt surface. The electron transfer between superoxide dismutase and the carboxymethylcellulose-gelatin-Pt wihout Fe(CN)(6)(4-/3-) and carboxymethylcellulose-gelatin-Pt, carboxymethylcellulose-gelatin-TiO(2)-Pt with Fe(CN)(6)(4-/3-) is quasireversible with a formal potential of 200 mV, 207 mV, and 200 mV vs Ag|AgCl respectively. The anodic (ks(a)) and cathodic (ks(c)) electron transfer rate constants and the anodic (α(a)) and cathodic (α(c)) transfer coefficients were evaluated: ks(a)=6.15 s(-1), α(a)=0.79, and ks(c)=1.48 s(-1) α(c)=0.19 for carboxymethylcellulose-superoxide dismutase without Fe(CN)(6)(4-/3-), ks(a)=6.77 s(-1), α(a)=0.87, and ks(c)=1 s(-1) α(c)=0.13 for carboxymethylcellulose-superoxide dismutase with Fe(CN)(6)(4-/3-), ks(a)=6.85 s(-1), α(a)=0.88, and ks(c)=0.76 s(-1) α(c)=0.1 carboxymethylcellulose-gelatin-TiO(2)-superoxide dismutase. The electron transfer rate between superoxide dismutase and the Pt electrode is remarkably enhanced due to immobilizing superoxide dismutase in carboxymethylcellulose-gelatin and TiO(2) nanoparticles tend to act like nanoscale electrodes., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Parapharyngeal space tumors are rare, accounting for 0.5% of head and neck neoplasms. Most of them are benign and originate in the salivary glands, especially the pleomorphic adenoma. We presented a 47-year-old man with parotid tail pleomorphic adenoma extending to the parapharyngeal space. The patient applied to our clinic with the complaints of a painless mass on his neck and in his mouth for 3 months. After fine needle aspiration biopsy, the mass was diagnosed as pleomorphic adenoma. The patient was hospitalized and operated in our clinic. As we see in literature review, parapharyngeal space tumors are rare, and most of them are pleomorphic adenomas arising from the deep lobe of the parotid gland and extend into the PPS.

Chronic paranasal sinus disease is one of the most common causes of application to physicians in pediatric and adult patients. In the surgical treatment of these diseases, endoscopic sinus surgery is an application that is often done to increase the quality of the patient's life. On account of this, the anatomic variations in skull basement must be well known to avoid possible major complications that may occur during the operation. Recent developments in paranasal sinus surgery also enhanced the need for examining exhaustively the anatomy of this region and existing pathology. Superiority of computed tomography (CT) has an unquestionable importance for the evaluation of anatomic structure and pathology compared with conventional radiographs. A likely anatomic knowledge is needed for a safe surgery. Before the surgery, determining the anatomic variations makes the operation safer and increases the prospects, so we can prevent complications that may occur during the surgery. In this study, CT coronal sections of 300 patients who were admitted to the Department of Ear Nose Throat of Medical Faculty of Cumhuriyet University Research and Training Hospital between the dates December 2008 and January 2011 with complaints of nasal flow and postnasal drip were studied. According to coronal section CT examinations, the patients were divided into 2 groups. Group 1, with 156 cases (64%), showed mucosal changes, and in 144 cases (36%), no mucosal changes were established (group 2). In comparison between the sexes, in groups 1 and 2 females, significant difference was determined for other parameters except the average height of the ethmoid roof. In the comparison between the sexes, in groups 1 and 2 males, significant difference was determined for all parameters. The difference between these 2 rates was statistically significant. Keros types 1 and 2 cases were compared with the control group, and there was no statistically significant difference. Notwithstanding, at the comparison of the Keros type 3 with the control group, there was a statistically significant difference for all the parameters (maximum orbital height, the length of the middle concha, and the nasal wall). It seems to be important for us to know the average length of the peripheral anatomic structures to avoid serious complications that may occur during the operation. Careful preoperative review of paranasal sinus CT scans in patients undergoing sinus surgery seems to be the most important to prevent severe intraoperative complications.

In this paper, attribute weighting method based on the cluster centers with aim of increasing the discrimination between classes has been proposed and applied to nonlinear separable datasets including two medical datasets (mammographic mass dataset and bupa liver disorders dataset) and 2-D spiral dataset. The goals of this method are to gather the data points near to cluster center all together to transform from nonlinear separable datasets to linear separable dataset. As clustering algorithm, k-means clustering, fuzzy c-means clustering, and subtractive clustering have been used. The proposed attribute weighting methods are k-means clustering based attribute weighting (KMCBAW), fuzzy c-means clustering based attribute weighting (FCMCBAW), and subtractive clustering based attribute weighting (SCBAW) and used prior to classifier algorithms including C4.5 decision tree and adaptive neuro-fuzzy inference system (ANFIS). To evaluate the proposed method, the recall, precision value, true negative rate (TNR), G-mean1, G-mean2, f-measure, and classification accuracy have been used. The results have shown that the best attribute weighting method was the subtractive clustering based attribute weighting with respect to classification performance in the classification of three used datasets.

Primary malignant melanoma of the nose and paranasal sinus mucosa is a rare disease and seen in less than 1% among all melanomas. Malignant melanomas have 2 origins: cutaneous and mucosal. The mucosal form has a worse prognosis because of its aggressiveness compared with that of the cutaneous form. Mucosal melanomas often occur at a rate of 2% to 3% among all melanomas and are typically found in the nasal cavity and paranasal sinuses. Generally, it is more common in males and in those older than 50 years. In this study, 4 patients were observed at the Cumhuriyet University Faculty of Medicine; 2 of them were a 64-year-old man and an 82-year-old woman who had a malignant melanoma originating from the nasal septal mucosa, 1 patient was a 72-year-old woman whose malignant melanoma originated from the inferior turbinate, and 1 patient was a 77-year-old woman with a sinonasally located melanoma. The conditions of these patients were discussed under the light of literature instructions.

An 18-year-old female came to our clinic with complaints of a tender lump just under her jaw on the left side and another lump in front of her left ear, ecchymosis around the eye and some redness in the eye at the same side. After administering antibiotic therapy for two days we suspected of tularemia and referred the patient to the Infectious Diseases Department. A serum sample was taken and a fine needle aspiration biopsy was performed. The patient was diagnosed with tularemia, the oculoglandular syndrome of Parinaud. Tularemia should also be kept in mind for differential diagnosis in patients with both ocular and glandular symptoms in endemic regions like Turkey and the appropriate therapy should be initiated immediately.

Artificial Immune Recognition System (AIRS) classifier algorithm is robust and effective in medical dataset classification applications such as breast cancer, heart disease, diabetes diagnosis etc. In our previous work, we have proposed a new resource allocation mechanism called fuzzy resource allocation in AIRS algorithm both to improve the classification accuracy and to decrease the computation time in classification process. Here, AIRS and Fuzzy-AIRS classifier algorithms and one against all approach have been combined to increase the classification accuracy of obstructive sleep apnea syndrome (OSAS) that is an important disease that influences both the right and the left cardiac ventricle. The OSAS dataset consists of four classes including of normal (25 subjects), mild OSAS (AHI (Apnea and Hypoapnea Index) = 5-15 and 14 subjects), moderate OSAS (AHI < 15-30 and 18 subjects), and serious OSAS (AHI > 30 and 26 subjects). In the extracting of features that is characterized the OSAS disease, the clinical features obtained from Polysomnography used diagnostic tool for obstructive sleep apnea in patients clinically suspected of suffering from this disease have been used. The used clinical features are Arousals Index (ARI), Apnea and Hypoapnea Index (AHI), SaO2 minimum value in stage of REM, and Percent Sleep Time (PST) in stage of SaO2 intervals bigger than 89%. Even though AIRS and Fuzzy-AIRS classifiers have been used in the classifying multi-class problems, theirs classification performances are low in the case of multi-class classification problems. Therefore, we have used two classes in AIRS and Fuzzy-AIRS classifiers by means of one against all approach instead of four classes comprising the healthy subjects, mild OSAS, moderate OSAS, and serious OSAS. We have applied the AIRS, Fuzzy-AIRS, AIRS with one against all approach (Pairwise AIRS), and Fuzzy-AIRS with one against all approach (Pairwise Fuzzy-AIRS) to OSAS dataset. The obtained classification accuracies are 63.41%, 63.41%, 87.19%, and 84.14% using the above methods for 200 resources, respectively. These results show that the best method for diagnosis of OSAS is the combination of AIRS and one against all approach (Pairwise AIRS).

Obstructive sleep apnea syndrome (OSAS) is an important disease that affects both the right and the left cardiac ventricle. This paper presents a novel classification method called pairwise ANFIS based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and one against all method for detecting the obstructive sleep apnea syndrome. In order to extract the features related with OSAS, we have used the clinical features obtained from Polysomnography device as a diagnostic tool for obstructive sleep apnea (OSA) in patients clinically suspected of suffering from this disease. The clinical features obtained from Polysomnography Reports are Arousals Index (ARI), Apnea and Hypoapnea Index (AHI), SaO2 minimum value in stage of REM, and Percent Sleep Time (PST) in stage of SaO2 intervals bigger than 89%. Since ANFIS has output with one class, we have extended the output of ANFIS to multi class by means of one against all method to diagnose the OSAS that has four classes consisting of normal (25 subjects), mild OSAS (AHI=5-15 and 14 subjects), middle OSAS (AHI<15-30 and 18 subjects), and heavy OSAS (AHI>30 and 26 subjects). The classification accuracy, sensitivity and specifity analysis, mean square error, and confusion matrix have been used to test the performance of proposed method. The obtained classification accuracies are 82.92%, 82.92%, 85.36%, and 87.80% for each class including normal, mild OSAS, middle OSAS, and heavy OSAS using ANFIS with one against all method with 50-50% train-test split, respectively. Combining ANFIS and one against all method that is firstly proposed by us was firstly applied for diagnosing the OSAS. The proposed method has produced very promising results in the detecting the obstructive sleep apnea syndrome.

Percutaneous extraction of intravascular foreign bodies with the help of specifically designed devices is the standard method of treatment and should be attempted in appropriate cases before any surgical approach. The majority of retrieved materials are catheter fragments localized in the superior vena cava, right side of the heart, or pulmonary artery. During diagnostic coronary angiography of a 65-year-old man, a short, 0.038-inch guide wire was identified in the right common iliac artery. It was erroneously left there during arterial monitoring performed at another center. The guide wire was successfully removed percutaneously using a combination of "wire-balloon" technique without any available specifically designed device.

The optic nerve disease is an important disease that appears commonly in public. In this paper, we propose a hybrid diagnostic system based on discretization (quantization) method and classification algorithms including C4.5 decision tree classifier, artificial neural network (ANN), and least square support vector machine (LSSVM) to diagnose the optic nerve disease from Visual Evoked Potential (VEP) signals with discrete values. The aim of this paper is to investigate the effect of Discretization method on the classification of optic nerve disease. Since the VEP signals are non-linearly-separable, low classification accuracy can be obtained by classifier algorithms. In order to overcome this problem, we have used the Discretization method as data pre-processing. The proposed method consists of two phases: (i) quantization of VEP signals using Discretization method, and (ii) diagnosis of discretized VEP signals using classification algorithms including C4.5 decision tree classifier, ANN, and LSSVM. The classification accuracies obtained by these hybrid methods (combination of C4.5 decision tree classifier-quantization method, combination of ANN-quantization method, and combination of LSSVM-quantization method) with and without quantization strategy are 84.6-96.92%, 94.20-96.76%, and 73.44-100%, respectively. As can be seen from these results, the best model used to classify the optic nerve disease from VEP signals is obtained for the combination of LSSVM classifier and quantization strategy. The obtained results denote that the proposed method can make an effective interpretation and point out the ability of design of a new intelligent assistance diagnosis system.

Objective: This paper presents a new method based on combining principal component analysis (PCA) and adaptive network-based fuzzy inference system (ANFIS) to diagnose the optic nerve disease from visual-evoked potential (VEP) signals. The aim of this study is to improve the classification accuracy of ANFIS classifier on diagnosis of optic nerve disease from VEP signals. With this aim, a new classifier ensemble based on ANFIS and PCA is proposed., Methods and Material: The VEP signals dataset include 61 healthy subjects and 68 patients suffered from optic nerve disease. First of all, the dimension of VEP signals dataset with 63 features has been reduced to 4 features using PCA. After applying PCA, ANFIS trained using three different training-testing datasets randomly with 50-50% training-testing partition., Results: The obtained classification results from ANFIS trained separately with three different training-testing datasets are 96.87%, 98.43%, and 98.43%, respectively. And then the results of ANFIS trained with three different training-testing datasets randomly with 50-50% training-testing partition have been combined with three different ways including weighted arithmetical mean that proposed firstly by us, arithmetical mean, and geometrical mean. The classification results of ANFIS combined with three different ways are 98.43%, 100%, and 100%, respectively. Also, ensemble ANFIS has been compared with ANN ensemble. ANN ensemble obtained 98.43%, 100%, and 100% prediction accuracy with three different ways including arithmetical mean, geometrical mean and weighted arithmetical mean., Conclusion: These results have shown that the proposed classifier ensemble approach based on ANFIS trained with different train-test datasets and PCA has produced very promising results in the diagnosis of optic nerve disease from VEP signals.

In this paper, we have compared the classifier algorithms including C4.5 decision tree, le artificial neural network (ANN), artificial immune recognition system (AIRS), and adaptive neuro-fuzzy inference system (ANFIS) in the diagnosis of obstructive sleep apnea syndrome (OSAS), which is an important disease that affects both the right and the left cardiac ventricle. The goal of this study was to find the best classifier model on the diagnosis of OSAS. The clinical features were obtained from Polysomnography device as a diagnostic tool for obstructive sleep apnea in patients clinically suspected of suffering this disease in this study. The clinical features are arousals index, apneahypopnea index (AHI), SaO2 minimum value in stage of rapid eye movement, and percent sleep time in stage of SaO2 intervals bigger than 89%. In our experiments, a total of 83 patients (58 with a positive OSAS (AHI>5) and 25 with a negative OSAS such that normal subjects) were examined. The decision support systems can help to physicians in the diagnosing of any disorder or disease using clues obtained from signal or images taken from subject having any disorder. In order to compare the used classifier algorithms, the mean square error, classification accuracy, area under the receiver operating characteristics curve (AUC), and sensitivity and specificity analysis have been used. The obtained AUC values of C4.5 decision tree, ANN, AIRS, and ANFIS classifiers are 0.971, 0.96, 0.96, and 0.922, respectively. These results have shown that the best classifier system is C4.5 decision tree classifier on the diagnosis of obstructive sleep apnea syndrome.

In this paper, we have proposed a novel similarity-based weighting method (SBWM), which combines similarity measure and weighting based on trend association (WBTA) method proposed by Sun Yi et al. (ICNN&B international conference, vol 1, pp 266-269, 2005). The aim of this study is to improve the classification accuracy of atherosclerosis, which is a common disease among the public. The proposed method consists of three parts: (1) feature extraction part related with atherosclerosis disease using fast Fourier transformation (FFT) modeling and calculation of maximum frequency envelope of sonograms, (2) data pre-processing part using SBWM, including different similarity measures such as cosine amplitude method, max-min method, absolute exponential method, and exponential similarity coefficient, and (3) classification part using artificial immune recognition system (AIRS) and Fuzzy-AIRS classifier algorithms. While AIRS and Fuzzy-AIRS algorithms obtained 71.92 and 78.94% success rates, respectively, the combination of SBWM with classifier algorithms including AIRS and Fuzzy-AIRS obtained 100% success rate on all the similarity measures. These results show that SBWM has produced very promising results in the classification of atherosclerosis from carotid artery Doppler signals. In future, we will use a larger dataset to test the proposed method.

In this study, we proposed a new medical diagnosis system based on principal component analysis (PCA), k-NN based weighting pre-processing, and Artificial Immune Recognition System (AIRS) for diagnosis of atherosclerosis from Carotid Artery Doppler Signals. The suggested system consists of four stages. First, in the feature extraction stage, we have obtained the features related with atherosclerosis disease using Fast Fourier Transformation (FFT) modeling and by calculating of maximum frequency envelope of sonograms. Second, in the dimensionality reduction stage, the 61 features of atherosclerosis disease have been reduced to 4 features using PCA. Third, in the pre-processing stage, we have weighted these 4 features using different values of k in a new weighting scheme based on k-NN based weighting pre-processing. Finally, in the classification stage, AIRS classifier has been used to classify subjects as healthy or having atherosclerosis. Hundred percent of classification accuracy has been obtained by the proposed system using 10-fold cross validation. This success shows that the proposed system is a robust and effective system in diagnosis of atherosclerosis disease.

Background: Liver injury caused by ischemia-reperfusion (I/R) processes is a complication of hepatic resection surgery and transplantation, particularly using grafts from marginal donors. Despite improvements in organ preservation and advances in surgical techniques, I/R injury remains a significant clinical problem. In this study, we investigated whether aprotinin provided protection against the adverse effects of I/R injury in liver tissue., Methods: Forty rats were randomized into four groups (n = 10): group I: (control group) I/R + no medication; group II: sham-operated group + no medication or I/R; group III: I/R + aprotinin; group IV: I/R + alpha-tocopherol. Malondialdehyde (MDA) was measured in the liver tissue and superoxide dismutase (SOD), catalase (CAT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), as well as lactate dehydrogenase (LDH) in rat serum., Results: Administration of aprotinin and alpha-tocopherol before I/R resulted in significant reductions of MDA levels compared to the I/R alone group (group I; P = .01 and P < .01, respectively). Administration of aprotinin or alpha-tocopherol prior to I/R resulted in significant increases in SOD and CAT levels compared with the I/R group (P < .05 each). Compared to the I/R group, significant decreases in plasma AST, ALT, and LDH levels were observed both in the aprotinin and in the alpha-tocopherol group (P < .05). Histological evaluation revealed the injury grade to be relatively lower among groups III and IV compared to group I., Discussion: In conclusion, rat hepatic structures in aprotinin and alpha-tocopherol administered groups were well protected. Therefore, aprotinin may provide protection against the adverse effects of I/R injury in liver transplantation.

Alveolar echinococcosis (AE) is a chronic and serious, even lethal, parasitic infection caused by the helminth Echinococcus multilocularis (EM). AE is an endemic disease in Turkey and it is particularly common in people living in the eastern Anatolia Region. In addition to various clinical presentations, symptoms which lead to diagnosis, however, are usually associated with the metastatic lesions. We herein reported a 62-year-old man who had liver alveolar hydatid disease with simultaneous lung and brain metastasis. We think there was only one therapeutic option, namely medical treatment with albendazol, which is the usual treatment for patients living in eastern Anatolia and who are admitted late resulting in a subsequent inoperable situation. Thus, radiological screening studies for the public in this region may increase the possibility of surgical treatment for alveolar hydatid disease.

In this paper, we have investigated the effect of generalized discriminate analysis (GDA) on classification performance of optic nerve disease from visual evoke potentials (VEP) signals. The GDA method has been used as a pre-processing step prior to the classification process of optic nerve disease. The proposed method consists of two parts. First, GDA has been used as pre-processing to increase the distinguishing of optic nerve disease from VEP signals. Second, we have used the C4.5 decision tree classifier, Levenberg Marquart (LM) back propagation algorithm, artificial immune recognition system (AIRS), linear discriminant analysis (LDA), and support vector machine (SVM) classifiers. Without GDA, we have obtained 84.37%, 93.75%, 75%, 76.56%, and 53.125% classification accuracies using C4.5 decision tree classifier, LM back propagation algorithm, AIRS, LDA, and SVM algorithms, respectively. With GDA, 93.75%, 93.86%, 81.25%, 93.75%, and 93.75% classification accuracies have been obtained using the above algorithms, respectively. These results show that the GDA pre-processing method has produced very promising results in diagnosis of optic nerve disease from VEP signals.

This paper presents a hybrid approach based on feature selection, fuzzy weighted pre-processing and artificial immune recognition system (AIRS) to medical decision support systems. We have used the heart disease and hepatitis disease datasets taken from UCI machine learning database as medical dataset. Artificial immune recognition system has shown an effective performance on several problems such as machine learning benchmark problems and medical classification problems like breast cancer, diabetes, and liver disorders classification. The proposed approach consists of three stages. In the first stage, the dimensions of heart disease and hepatitis disease datasets are reduced to 9 from 13 and 19 in the feature selection (FS) sub-program by means of C4.5 decision tree algorithm (CBA program), respectively. In the second stage, heart disease and hepatitis disease datasets are normalized in the range of [0,1] and are weighted via fuzzy weighted pre-processing. In the third stage, weighted input values obtained from fuzzy weighted pre-processing are classified using AIRS classifier system. The obtained classification accuracies of our system are 92.59% and 81.82% using 50-50% training-test split for heart disease and hepatitis disease datasets, respectively. With these results, the proposed method can be used in medical decision support systems.

Carotid Artery Doppler Signals were recorded from 114 subjects, 60 of whom had Atherosclerosis disease while the rest were healthy controls. Diagnosis of Atherosclerosis from Carotid Artery Doppler Signals was conducted using Fuzzy weighted pre-processing and Least Square Support Vector Machine (LSSVM). First, in order to determine the LSSVM inputs, spectral analysis of Carotid Artery Doppler Signals was performed via Autoregressive (AR) modeling. Then, fuzzy weighted pre-processing based is proposed expert system, applied to inputs obtained from spectral analysis of Carotid Artery Doppler Signals. LSSVM was used to detect Atherosclerosis from Carotid Artery Doppler Signals. All data set were obtained from Carotid Artery Doppler Signals of healthy subjects and subjects suffering from Atherosclerosis disease. The employed expert system has achieved 100% classification accuracy using a 10-fold Cross Validation (CV) method.

The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. Such a disease is breast cancer, which is a very common type of cancer among woman. As the incidence of this disease has increased significantly in the recent years, machine learning applications to this problem have also took a great attention as well as medical consideration. This study aims at diagnosing breast cancer with a new hybrid machine learning method. By hybridizing a fuzzy-artificial immune system with k-nearest neighbour algorithm, a method was obtained to solve this diagnosis problem via classifying Wisconsin Breast Cancer Dataset (WBCD). This data set is a very commonly used data set in the literature relating the use of classification systems for breast cancer diagnosis and it was used in this study to compare the classification performance of our proposed method with regard to other studies. We obtained a classification accuracy of 99.14%, which is the highest one reached so far. The classification accuracy was obtained via 10-fold cross validation. This result is for WBCD but it states that this method can be used confidently for other breast cancer diagnosis problems, too.

Background: Incisional hernias still continue to be a serious problem for surgeons. In this study, we aimed to investigate the effects of polypropylene mesh and mersilene mesh, which are frequently employed in incisional hernias, as well as the effects of their application techniques on late complications., Methods: Two-hundred-sixty-four open abdominal hernia repairs were performed between 1986--2000, using prosthetic materials: polypropylene mesh and mersilene mesh were used in hernia repair. Mesh was placed as onlay, underlay and sandwich techniques. Follow-up data were obtained from medical records., Results: Comparisons were made with respect to surgical techniques and to late complications such as recurrence, enterocutaneous fistula, intestinal obstruction, and infections. Enterocutaneous fistulas developed in two patients. Recurrence occurred in 6.4 per cent. Chronic infection and wound sinus formation occurred in 5 per cent. The causes of recurrence included smoking, cellulitis, chronic infection/sinus tract, upper abdominal localization, and obstruction. Fistula formation occurred in patients with no peritoneal prevention, which was statistically significant (p=0.012). Chronic infection/sinus tract was high in patients for whom mersilene mesh was used, and enterocutaneous fistula occurred in 2 patients., Conclusion: To prevent late complications, it is necessary to avoid the contact of mesh with bowel.

The electrochemical reduction of 1-([(4-halophenyl)imino]methyl)-2-naphthols on graphite electrodes was studied using cyclic voltammetry, chronoamperometry, constant-potential coulometry and preparative constant-potential electrolysis techniques. The data revealed that the reduction on graphite was irreversible and followed an EC mechanism. The diffusion coefficients and the number of electrons transferred were determined using the chronoamperometric Cottrell slope and the ultramicro disc Pt-electrode steady-state current. The number of electrons was also determined by bulk electrolysis. The compounds were subjected to constant-potential preparative electrolysis and the electrolysis products were purified and identified by spectroscopic methods. Based on these findings, a mechanism for the electro-reduction process is proposed.

Tuberculous liver abscess (TLA) is an extremely rare condition, even in the country where tuberculosis is an alarming public health problem. Primary TLA, with no evidence of infection elsewhere, is even less common. Herein, we report a case with primary TLA and review the literature.

Background: Previously surgical operation was the only accepted treatment for hydatid liver cysts. Recently percutaneous management has become more preferable because of its low morbidity rate and lower cost., Patients and Methods: In all, 101 patients harbouring 120 hydatid cysts of the liver were treated by percutaneous drainage between October 1994 and December 1997. Of these cysts, 89 were in the right liver and 31 in the left liver.Thirty-one patients had had previous operations for hydatid disease. All cysts had an anechoic or hypoechoic unilocular appearance on ultrasound scan. The mean dimension of the cysts was 7.5+/-2.9 cm (range 3-10.4 cm). All patients received oral albendazole 10 mg/kg perioperatively. After aspiration under sonographic guidance, cysts were irrigated with 95% ethanol., Results: The amount of cyst fluid aspirated was 220+/-75 ml and the amount of irrigation solution used was 175+/-42 ml. Four patients developed mild fever and three had urticaria. Mean length of hospital stay was 2.1+/-0.7 (range 1-4) days, and patients were followed up for 43-62 months (mean 54+/-5.4 months). Maximal cyst diameter decreased from 7.5+/-2.9 cm to 3.2+/-15 cm (p<0.001). Sonographic examinations revealed high-level heterogeneous echoes in the cyst cavity (heterogeneous echo pattern), while the cyst cavity was completely obliterated by echogenic material (pseudotumour echo pattern)., Discussion: Most hydatid cysts of the liver can be managed successfully by a combination of drug therapy and percutaneous drainage.

Purpose: To evaluate the results of the surgical treatment of hepatic injuries in our institution for liver injuries., Patients and Methods: One hundred seventy four patients who underwent operations between January 1986-December 1999 in Atatürk University Medical School, Emergency Service were reviewed retrospectively., Results: 135 patients were male (77.5%). The mean age was 25.4 (range 3-84). Sixty three patients (36.3%) had only hepatic injuries and the others had co-existing abdominal organ injury [62 patients (35.7%) had one organ, 29 (16.7%) had two, 17 (9.7%) had three, 2 (1.1%) had four, and 1 (0.5%) had 5 organ injuries]. Five patients (2.8%) had inferior vena cava and 1 (0.5%) had vena porta injuries. One hundred seven patients (61.4%) had blunt, 44 (25.3%) had stab wound and 23 (13.3%) had gunshot injuries. Management was simple suture in 104 patient (60%), primary suture + surgical cell patching in 52 (29.8%), hepatectomy (5 right hepatectomy, 5 non anatomic hepatectomy) in 10 (5.7%), perihepatic packing in 4 (2.3%), primary suture + omental patch in 2 (1.1%), primary suture + arterial ligation in 2 (1.1%). Eleven patients (16.4%) in penetrating trauma group "Penetrating Abdominal Trauma Index" (PATI) score were higher than 25. Fever was the most common complaint postoperatively (5%). Three patients (1.7%) underwent reoperation. Twenty-six patients (14.9%) which one of them ware died. Died in the postoperative periods, 23 (13.2%) had blunt and 3 (1.7%) had penetrating traumas., Conclusion: Liver trauma still has high mortality rate injuries are very momentous. Especially blunt trauma related hepatic.

The addition of daclizumab (a human immunoglobulin G1 monoclonal antibody that blocks interleukin-2 receptors on T lymphocytes) to mycophenolate mofetil (MMF) and steroids is a new option for initial immunosuppression in patients undergoing liver transplantation (LT) with impaired renal function. We evaluated the efficacy and safety of daclizumab in preventing rejection in 25 patients with impaired kidney function undergoing LT. Patients with serum creatinine (Cr) levels greater than 2 mg/dL immediately before LT were administered initial immunosuppression with daclizumab, 1 mg/kg, in addition to MMF, 2 g/d, and methylprednisolone. Tacrolimus was added after kidney function improved (when Cr levels improved by >25% of initial value). Daclizumab-treated patients were compared retrospectively with 2 other groups of patients who underwent LT with kidney impairment (Cr > 2 mg/dL): 56 patients were administered OKT3 induction, and 48 patients were administered low-dose tacrolimus. The incidence of rejection and infection (bacterial, fungal, and viral), need for preoperative and postoperative dialysis, Cr level immediately post-LT and at 3 months, and graft and patient survival were analyzed. There was no difference among the groups in 3-month Cr levels or the incidence of rejection or fungal or viral infection. The daclizumab group had fewer bacterial infections (n = 13) than the tacrolimus group (n = 28) and significantly fewer than the OKT3 group (n = 58; P =.006). Only 1 patient (4%) in the daclizumab group required dialysis post-LT versus 13 patients in each of the other groups (OKT3, 23.21%; P <.05; tacrolimus, 27%). In the daclizumab group, 2-year patient and graft survival rates were statistically significant compared with the low-dose tacrolimus group (89% and 81% v 73% and 69%, respectively; P =.06). There were no side effects related to daclizumab use, and all patients tolerated the drug well. In patients with impaired renal function before LT, daclizumab-based initial immunosuppression can be used safely to reduce the risk for infection and need for dialysis post-LT, with improved long-term graft and patient survival.

Two hundred forty-eight patients were operated for perforated peptic ulcer between 1983 and 1998. Of the patients 112 (45.1%) had chronic, 34 (13.7%) had acute ulcer history and 102 (41.2%) had no ulcer history. Of the patients 228 (92.0%) had duodenal, 9 (3.6%) had juxtapyloric, 6 (2.4%) had marginal, and 5 (2.0%) had antral ulcer. Forty two patients (16.9%) admitted within 12 hours and 206 patients (83.1%) between 12 hours and six days after perforation. Simple closure and omental patch was performed in 32 patients (12.9%) who had severe concomitant illness and 126 (50.8%) intraabdominal sepsis, truncal vagotomy + pyloroplasty in 32 (12.9%), simple closure + omental patch + truncal vagotomy + gastroenterostomy in 34 (13.7%), simple closure + omental patch + parietal cell vagotomy in 21 (8.5%), truncal vagotomy + antrectomy in 3 (1.2%). Patients who didn't have definitive procedure received H2 receptor blockers or proton pomp inhibitors. One hundred ninety-three patients (77.8%) underwent endoscopic control. Two of 53 patients with definitive procedure (3.8%) and 34 of 140 patients (24.3%) with simple closure had recurrence. Two patients in simple closure group underwent parietal cell vagotomy, the others received medical treatment. The recurrence rate was significantly higher in simple closure group (p < 0.01).