A corpus-based semantic kernel for text classification by using meaning values of terms

Text categorization plays a crucial role in both academic and commercial platforms due to the growing demand for automatic organization of documents. Kernel-based classification algorithms such as Support Vector Machines (SVM) have become highly popular in the task of text mining. This is mainly due to their relatively high classification accuracy on several application domains as well as their ability to handle high dimensional and sparse data which is the prohibitive characteristics of textual data representation. Recently, there is an increased interest in the exploitation of background knowledge such as ontologies and corpus-based statistical knowledge in text categorization. It has been shown that, by replacing the standard kernel functions such as linear kernel with customized kernel functions which take advantage of this background knowledge, it is possible to increase the performance of SVM in the text classification domain. Based on this, we propose a novel semantic smoothing kernel for SVM. The suggested approach is based on a meaning measure, which calculates the meaningfulness of the terms in the context of classes. The documents vectors are smoothed based on these meaning values of the terms in the context of classes. Since we efficiently make use of the class information in the smoothing process, it can be considered a supervised smoothing kernel. The meaning measure is based on the Helmholtz principle from Gestalt theory and has previously been applied to several text mining applications such as document summarization and feature extraction. However, to the best of our knowledge, ours is the first study to use meaning measure in a supervised setting to build a semantic kernel for SVM. We evaluated the proposed approach by conducting a large number of experiments on well-known textual datasets and present results with respect to different experimental conditions. We compare our results with traditional kernels used in SVM such as linear kernel as well as with several corpus-based semantic kernels. Our results show that classification performance of the proposed approach outperforms other kernels

Fuzzy-based PROMETHEE method for performance ranking of SARS-CoV-2 IgM antibody tests

This article belongs to the Special Issue Monitoring and Detection for SARS-CoV-2 and Its Variants.Antibody tests, widely used as a complementary approach to reverse transcriptase-polymerase chain reaction testing in identifying COVID-19 cases, are used to measure antibodies developed for COVID-19. This study aimed to evaluate the different parameters of the FDA-authorized SARS-CoV-2 IgM antibody tests and to rank them according to their performance levels. In the study, we involved 27 antibody tests, and the analyzes were performed using the fuzzy preference ranking organization method for the enrichment evaluation model, a multi-criteria decision-making model. While criteria such as analytical sensitivity, specificity, positive predictive value, and negative predictive value were evaluated in the study, the ranking was reported by determining the importance levels of the criteria. According to our evaluation, Innovita 2019-nCoV Ab Test (colloidal gold) was at the top of the ranking. While Cellex qSARS-CoV-2 IgG/IgM Rapid Test and Assure COVID-19 IgG/IgM Rapid Tester ranked second and third on the list, the InBios-SCoV 2 Detect Ig M ELISA Rapid Test Kit was determined as the least preferable. The fuzzy preference ranking organization method for enrichment evaluation, which has been applied to many fields, can help decision-makers choose the appropriate antibody test for managing COVID-19 in controlling the global pandemic

Comparison of Opinions and Practices of Pediatric Intensive Care and Pediatric Emergency Departments in High-flow Nasal Cannula Oxygen Therapy: A National Survey Study

Introduction:The purpose of this study is to compare the practice and opinions of tertiary pediatric intensive care units and pediatric emergency departments on high flow nasal cannula oxygen therapy in Turkey.Methods:A questionnaire was sent to the clinical chiefs of the tertiary intensive care units or pediatric emergency departments who are members of the Pediatric Emergency and Intensive Care Association via e-mail. In the questionnaire, the features of the unit, the high-flow nasal cannula oxygen therapy practice and their opinions on this treatment were asked. Pathologies using highflow nasal cannula and the success expected were asked to score between 0 and 10 (0: Completely ineffective; 10: Very effective).Results:A total of 14 pediatric intensive care units and 17 pediatric emergency departments were included in the study. The most frequently used and the highest success score belonged to bronchiolitis. It is used more frequently for neuromuscular diseases in emergency departments (p0.05). In the follow-up, intensive care units use the chest radiography and the emergency departments use a respiratory severity score more frequently (p<0.05). Complication of air leak syndrome was more common in intensive care units (35.7% vs. 0; p<0.05). All units described high-flow nasal cannula oxygen therapy as an easy-to-use method. 94.1% of the emergency departments and all intensive care units stated that the treatment was comfortable for the patient.Conclusion:High flow nasal cannula oxygen therapy is used in various pathologies that cause respiratory distress. The treatment practice of the units partially overlaps. It is considered to be easy to apply, comfortable and effective treatment for patients

Metinsel veri madenciliği için anlamsal yarı-eğitimli algoritmaların geliştirilmesi

Ganiz, Murat Can (Dogus Author) -- Zeynep Hilal, Kilimci (Dogus Author)Metinsel veri madenciliği büyük miktarlardaki metinsel verilerden faydalı bilgilerin çıkarılması veya bunların otomatik olarak organize edilmesini içerir. Büyük miktarlarda metinsel belgenin otomatik olarak organize edilmesinde metin sınıflandırma algoritmaları önemli bir rol oynar. Bu alanda kullanılan sınıflandırma algoritmaları “eğitimli” (supervised), kümeleme algoritmaları ise “eğitimsiz” (unsupervised) olarak adlandırılırlar. Bunların ortasında yer alan “yarı-eğitimli” (semisupervised) algoritmalar ise etiketli verinin yanı sıra bol miktarda bulunan etiketsiz veriden faydalanarak sınıflandırma başarımını arttırabilirler. Metinsel veri madenciliği algoritmalarında geleneksel olarak kelime sepeti (bag-of-words) olarak tabir edilen model kullanılmaktadır. Kelime sepeti modeli metinde geçen kelimeleri bulundukları yerden ve birbirinden bağımsız olarak değerlendirir. Ayrıca geleneksel algoritmalardaki bir başka varsayım ise metinlerin birbirinden bağımsız ve eşit olarak dağıldıklarıdır. Sonuç olarak bu yaklaşım tarzı kelimelerin ve metinlerin birbirleri arasındaki anlamsal ilişkileri göz ardı etmektedir. Metinsel veri madenciliği alanında son yıllarda özellikle kelimeler arasındaki anlamsal ilişkilerden faydalanan çalışmalara ilgi artmaktadır. Anlamsal bilginin kullanılması geleneksel makine öğrenmesi algoritmalarının başarımını özellikle eldeki verinin az, seyrek veya gürültülü olduğu durumlarda arttırmaktadır. Gerçek hayat uygulamalarında algoritmaların eğitim için kullanacağı veri genellikle sınırlı ve gürültülüdür. Bu yüzden anlamsal bilgiyi kullanabilen algoritmalar gerçek hayat problemlerinde büyük yarar sağlama potansiyeline sahiptir. Bu projede, ilk aşamada eğitimli metinsel veri madenciliği için anlamsal algoritmalar geliştirdik. Bu anlamsal algoritmalar metin sınıflandırma ve özellik seçimi alanlarında performans artışı sağlamaktadır. Projenin ikinci aşamasında ise bu yöntemlerden yola çıkarak etiketli ve etiketsiz verileri kullanan yarı-eğitimli metin sınıflandırma algoritmaları geliştirme faaliyetleri yürüttük. Proje süresince 5 yüksek lisans tezi tamamlanmış, 1 Doktora tezi tez savunma aşamasına gelmiş, 2 adet SCI dergi makalesi yayınlanmış, 8 adet bildiri ulusal ve uluslararası konferanslar ve sempozyumlarda sunulmuş ve yayınlanmıştır. Hazırlanan 2 adet dergi makalesi ise dergilere gönderilmiş ve değerlendirme aşamasındadır. Projenin son aşamasındaki bulgularımızı içeren 1 adet konferans bildirisi 2 adet dergi makalesi de hazırlık aşamasındadır. Ayrıca proje ile ilgili olarak üniversite çıkışlı bir girişim şirketi (spin-off) kurulmuştur.Textual data mining is the process of extracting useful knowledge from large amount of textual data. In this field, classification algorithms are called supervised and clustering algorithms are called unsupervised algorithms. Between these there are semi supervised algorithms which can improve the accuracy of the classification by making use of the unlabeled data. Traditionally, bag-of-words model is being used in textual data mining algorithms. Bag-of-words model assumes that words independent from each other and their positions in the text. Furthermore, traditional algorithms assume that texts are independent and identically distributed. As a result this approach ignores the semantic relationship between words and between texts. There has been a recent interest in works that make use of the semantic relationships especially between the words. Use of semantic knowledge increase the performance of the systems especially when there are few, sparse and noisy data. In fact, there are very sparse and noisy data in real world settings. As a result, algorithms that can make use of the semantic knowledge have a great potential to increase the performance. In this project, in the first phase, we developed semantic algorithms and methods for supervised classification. These semantic algorithms provide performance improvements on text classification and feature selection. On the second phase of the project we have pursued development activities for semi-supervised classification algorithms that make use of labeled and unlabeled data, based on the methods developed in the first phase. During the project, 5 master’s thesis is completed, the PhD student is advanced to the dissertation defense stage, two articles are published on SCI indexed journals, 8 proceedings are presented in national and international conferences. Two journal articles are sent and 1 conference proceeding and two journal articles are in preparation, which include the findings of the last phase of the project. Furthermore, a spin-off technology company is founded related to the project.TÜBİTA

Evaluation of Clinical and Radiological Indicators of Childhood Head Trauma

Objective: The aim of this study is to determine the clinical signs of traumatic brain injury and its long-term effects on prognosis by evaluating the clinical and radiological findings of the patients admitted to the pediatric emergency department due to blunt head trauma. Method: The cases who applied to the pediatric emergency department due to head trauma were examined prospectively. Glaskow Coma (GCS) and Pediatric Trauma Scores (PTS) were calculated. The patients were evaluated neurologically 6 months after they were discharged. Results: A total of 707 pediatric patients [mean age: 59.8 +- 42.6 months; range: 1 month to 13 years; 263 (37.2%) girls] were evaluated prospectively. Pathology was detected in 101 cases (45.9%) [(epidural hematoma, 14; subdural hematoma, 11; brain edema, 36; intracerebral hematoma, 6; subarachnoid hemorrhage, 8; cerebral contusion, 22. Seventy-two (10.1%) patients had skull fractures.] Seventeen cases (2.4%) were operated, and 7 (1.4%) cases were lost. In children aged &lt; 2 years vomiting, tachypnea, focal neurological findings, multitrauma, GCS &lt;15 and low PTS were more common with traumatic brain injury (p &lt;0.05). Vomiting, GCS &lt;15 and low PTS were more common in children &gt;2 years old and with traumatic brain injury (p &lt;0.05). Neurological sequelae were not detected in patients aged &lt;2 years with mild trauma. Loss of consciousness, pulse rate, respiratory and blood pressure abnormalities, focal neurological findings, low GCS and PTS were more common in children aged &gt;2 years and with neurological sequelae (p &lt;0.05). Conclusion: Physical examination findings, GCS, and PTS levels are useful tools in predicting the short- and long-term consequences of the injury

Periorbital Emphysema After Endoscopic Nasal Polyp Surgery

Periorbital and subcutaneous emphysema after transnasal endoscopic surgery are rare. Periorbital emphysema has been reported after facial trauma, dental interventions, procedures such as endoscopic sinus surgery and rhinoplasty, and due to medications such as systemic steroids. Although very rare, it may require urgent intervention because of the risk of increased intraocular pressure and impaired blood supply to the globe. The otolaryngology department requested ophthalmology consultation for a 65-year-old male patient who had severe periorbital emphysema of the right eye the day after endoscopic nasal polypectomy due to severe coughing and straining. Crepitus was detected on skin palpation and immediate intervention was performed by passing a 21-gauge needle through the skin into the subcutaneous tissue of the upper and lower eyelids to evacuate the subcutaneous air. The patient’s clinical symptoms resolved with no postoperative complications

A Rare Cardiotoxicity: Butane Inhalation

The number of cases of voluntary inhalation of volatile substances is increasing all over the world and in our country. This is a social health problem that can be encountered in different socioeconomic and cultural levels. The number of applications to pediatric emergency services cannot be underrated because the age of first use of such illegal substances has decreased gradually. Inhalation of volatile substances can cause pathologies in a very broad spectrum, including sudden death. In this paper, we report a case of cardiac arrest developing after lighter fluid inhalation

Does blood type have an effect on the course of COVID-19?

Introduction Predictive parameters that can affect the course of this infection have been the main topic of research since the beginning of the COVID-19 (Coronavirus disease 2019) pandemic. Since the discovery of blood groups, the effect of these on infectious diseases has always been of interest. Objectives To analyze the effect of ABO blood group on mortality, hospitalization duration and hematological and cytokine storm parameters in patients with COVID-19. Patients and methods: This retrospective study was conducted on 140 patients diagnosed with COVID-19. Demographic characteristics, laboratory parameters including ABO blood group, complete blood count (CBC) parameters, biochemical tests, cytokine storm parameters, duration of hospitalization, and final status (discharge or death) were recorded. Results: The 140 patients included in the analysis comprised 72 (51.4%) males and 68 (48.6%) females with a mean age of 66.3±14.0 years. . Age and gender, hospitalization duration and mortality rates were similar in all blood group types. Only D-dimer levels were found to be higher in blood group A compared with other blood groups. Conclusion: Although no difference in mortality was determined between groups, the D-dimer level was statistically significantly higher in COVID-19 patients with A blood group. Larger studies are needed to reflect D-dimer levels on the clinical course of infection, and thus on daily practice

Single Centre Experience: Bening and Malign Hematological Patients with COVID-19

Introduction Coronavirus disease 2019 (COVID-19) were declared as pandemic by World Health Organization. With this study, we aimed to define our patients who were followed up with malign or benign hematological diagnoses and diagnosed with COVID-19; determine the distribution of this infection in patient groups and contribute to the literature by creating descriptive statistics with its clinical and demographic features. Patients and methods: It is planned to retrospectively examine patients with a history of COVID-19 who were followed up in Hematology Department of Dışkapı Yıldırım Beyazıt Training and Research Hospital with benign and malignant diagnoses. Results: 88 patients who had COVID-19 infection while being followed in our clinic due to hematological diseases were included in the study. 77 patients had been followed by hematologic malignancies and 11 patients had been followed by benign hematological disease.In the group with malignancy, COVID was found most frequently in patients diagnosed with Philadelphia chromosome negative myeloproliferative neoplasms (22%), nonhodgkin lymphoma (19%) and multiple myeloma (16%). ITP (64%) was the most common disease in patients with benign hematological disorder who had COVID history. 52 (67%) of the malignant cases and 8 (73%) of the bening cases were found to be followed up with the disease in remission. The all patient's most common symptoms at COVID-19 diagnosis were fever (77%), cough (70%) and weakness (65%). 45% of the patients were isolated at home, 48% were required hospitalization. 49% of patients had mild; 27% had moderate and 24% had severe COVID-19 infection. Almost all of the patients in the moderate and severe disease group were followed up in patients diagnosed with malignant hematological disease. 16 (18%) patients received mechanical ventilation and 16 (18%) patients was transferred intensive care unit. All of the patients who were intubated and needed intensive care were diagnosed with malignant hematological disease. 17 patients died due to COVID-19 infection. The mortality rate was 22% in patients with diagnosis of malignant hematological diseases, and 19% when all patients (malignant and bening) were included. Conclusion: In conclusion, the COVID-19 pandemic is a problem all over the world. Determining the course of the disease in certain diagnostic groups is important in the management of both the main disease and the COVID-19 infection. Therefore, the contribution of such recording studies to the literature is important and valuable

Determination of Physicochemical Properties and Oxidative Stability of Rice Bran Oils

Bu çalışmada; stabilizasyon işleminin pirinç kepeği yağının fizikokimyasal özelliklerine ve yağ asidi bileşimine etkisinin belirlenmesi amaçlanmıştır. İki farklı pirinç kepeği çeşidi (Osmancık ve Opela); mikrodalga, etüv ve mikrodalga+etüv olmak üzere 3 farklı yöntemle stabilize edilmiştir. Pirinç kepekleri toplamda dokuz farklı stabilizasyon şartında muamele edilmiştir. Mikrodalga ile stabilizasyonda 600 W 1 dk, 600 W 2 dk, 600 W 3 dk; etüv ile stabilizasyonda 80°C’de 30dk, 100°C’de 30dk, 120°C’de 30dk, etüv ve mikrodalganın birlikte kullanıldığı kombine yöntemde ise 600 W 2dk mikrodalga+80°C’de 30dk etüv; 600 W 2dk mikrodalga+100°C’de 30dk etüv ve 600 W 2dk mikrodalga+120°C’de 30dk etüv uygulaması yapılmıştır. Stabilizasyon işleminden sonra pirinç kepek yağı solvent ekstraksiyon yöntemi ile elde edilmiştir. Elde edilen pirinç kepeği yağlarına ait serbest yağ asitliği değeri, peroksit sayısı, yağ asitleri bileşimi, sterol kompozisyonu, iyot sayısı, sabunlaşma sayısı, özgül ağırlık değeri ve kırılma indisi değeri belirlenmiştir. Uygulanan stabilizasyon işlemleri sonucunda pirinç kepeği yağlarının serbest yağ asitliği, peroksit sayısı ve iyot sayısı değerlerinin azaldığı tespit edilmiştir (p0,05). Pirinç kepeği yağında en çok bulunan sterol ?-sitosterol olarak tespit edilmiştir.In this research, it was aimed to determine the effects of stabilization on some physicochemical properties and fatty acid composition of rice bran oil. The rice bran samples (Osmancık and Opela) was stabilized under three ways (microwave, drying oven and microwave + drying oven) including nine conditions (drying oven: 80°C 30 min, 100°C 30 min, 120°C 30 min; microwave : 600 W 1 min, 600 W 2 min, 600 W 3 min; microwave + drying oven: 600 W 2 min microwave - 80°C 30 min drying oven, 600 W 2 min microwave - 100°C 30 min drying oven, 600 W 2 min microwave - 120°C 30 min drying oven). The rice bran oil was obtained by solvent extraction technology. The free fatty acids content, peroxide value, iodine number, saponification number, specific gravity, refractive index, fatty acid composition and the sterol composition of rice bran oil samples were determined. The acidity, peroxide value and iodine number of the oil samples were significantly decreased with the stabilization process applied (p0,05). ?-sitosterol was detected as the main sterol in rice bran oil