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Pair Annotation as a Novel Annotation Procedure: The Case of Turkish Discourse Bank
Demirşahin, Işın; Zeyrek Bozşahin, Deniz (2017-6-17)
In this chapter, we provide an overview of Turkish Discourse Bank, a resource of ∼∼400,000 words built on a sub-corpus of the 2-million-word METU Turkish Corpus annotated following the principles of Penn Discourse Tree Ban...
TDB 1.1: Extensions on Turkish Discourse Bank
Zeyrek Bozşahin, Deniz; Murathan, Murathan (2017-4-3)
In this paper we present the recent developments on Turkish Discourse Bank (TDB). We first summarize the resource and present an evaluation. Then, we describe TDB 1.1, i.e. enrichments on 10% of the corpus (namely, added s...
The evaluation of radiofrequency facet nerve denervation in the patients with lumbar facet syndrome: experience with 493 patients
Mimaroglu, Caner; Mimaroglu Altinay, Beste; Duger, Cevdet; Isbir, Ahmet Cemil; Gursoy, Sinan; KAYGUSUZ, KENAN; Kol, Iclal Ozdemir (2017-12-01)
Objective: Radio frequency thermocoagulation (RFT) is a relatively new modality and has been recommended for treatment of back pain diagnosed as to be originating from spinal facet joints. We aimed to evaluate the efficacy...
IDENTIFICATION OF DAMAGED WHEAT KERNELS AND CRACKED-SHELL HAZELNUTS WITH IMPACT ACOUSTICS TIME-FREQUENCY PATTERNS
Ince, N. F.; Onaran, I.; Pearson, T.; Tewfik, A. H.; ÇETİN, AHMET ENİS; Kalkan, H.; Yardimci, Y. (2008-07-01)
A new adaptive time-frequency (t-f) analysis and classification procedure is applied to impact acoustic signals for detecting hazelnuts with cracked shells and three types of damaged wheat kernels. Kernels were dropped ont...
Pain Detection from Facial Videos Using Two-Stage Deep Learning
Menchetti, Guglielmo; Chen, Zhanli; Wilkie, Diana J.; Ansari, Rashid; Yardimci, Yasemin; Cetin, A. Enis (2019-01-01)
A new method to objectively measure pain using computer vision and machine learning technologies is presented. Our method seeks to capture facial expressions of pain to detect pain, especially when a patients cannot commun...
Identification of Three Novel FBN1 Mutations and Their Phenotypic Relationship of Marfan Syndrome
KAYHAN, GÜLSÜM; ERGÜN, MEHMET ALİ; Ergun, Sezen Guntekin; KULA, SERDAR; PERÇİN, Ferda Emriye (Mary Ann Liebert Inc, 2018-07-26)
Background: Marfan syndrome (MS), a connective tissue disorder that affects ocular, skeletal, and cardiovascular systems, is caused by heterozygous pathogenic variants in FBN1. To date, over 1800 different pathogenic varia...
Graphical Passwords as Browser Extension: Implementation and Usability Study
BIÇAKCI, KEMAL; Yuceel, Mustafa; Erdeniz, Burak; Gurbaslar, Hakan; ATALAY, NART BEDİN (2009-06-19)
Today, most Internet applications still establish user authentication with traditional text based passwords. Designing a secure as well as a user-friendly password-based method has been on the agenda of security researcher...
Image-based retrieval system and computer-aided diagnosis system for renal cortical scintigraphy images
Mumcuoglu, Erkan; Nar, Fatih; Ugur, Oemer; BOZKURT, MURAT FANİ; Aslan, Mehmet (2008-02-19)
Cortical renal (kidney) scintigraphy images are 2D images (256x256) acquired in three projection angles (posterior, right-posterior-oblique and left-posterior-oblique). These images are used by nuclear medicine specialists...
Expression Levels of SMAD Specific E3 Ubiquitin Protein Ligase 2 (Smurf2) and its Interacting Partners Show Region-specific Alterations During Brain Aging
Tuz-Sasik, Melek Umay; Karoglu-Eravsar, Elif Tugce; Kinali, Meric; ARSLAN ERGÜL, AYÇA; ADAMS, MİCHELLE (Elsevier BV, 2020-06-01)
Aging occurs due to a combination of several factors, such as telomere attrition, cellular senescence, and stem cell exhaustion. The telomere attrition-dependent cellular senescence is regulated by increased levels of SMAD...
Adverse Drug Event Notification System Reusing clinical patient data for semi-automatic ADE detection
Krahn, Tobias; Eichelberg, Marco; Gudenkauf, Stefan; Erturkmen, Gokce B. Laleci; Appelrath, H. -Juergen;( Abstracts: Adverse drug events (ADEs) are common, costly and a public health issue. Today, their detection relies on medical chart review and spontaneous reports, but this is known to be rather ineffective. Along with the increasing availability of clinical patient data in electronic health records (EHRs), a computer-based ADE detection has a tremendous potential to contribute to patient safety. Current ADE detection systems are very specific, usually built directly on top of clinical information systems through proprietary interfaces. Thus, it is not possible to run different ADE detection tools on top of already existing systems in an ad-hoc manner. The European project "SALUS" aims at providing the necessary infrastructure and toolset for accessing and analyzing clinical patient data of heterogeneous clinical information systems. This paper highlights the SALUS ADE notification system as the key tool to enable a semi-automatic ADE detection and notification. In contrast to previous work, the ADE notification system is not restricted to a specific clinical environment. It can be run on different clinical data models with different levels of data quality. The system is equipped with innovative features, building up an intelligent, comprehensive ADE detection and notification system that promises a profound impact in the domain of computer-based ADE detection.; 2014-05-29)
Adverse drug events (ADEs) are common, costly and a public health issue. Today, their detection relies on medical chart review and spontaneous reports, but this is known to be rather ineffective. Along with the increasing ...