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https://www.readbyqxmd.com/read/28343209/terminological-collocations-in-medical-latin-and-english-a-comparative-study
#1
Olena M Bieliaieva, Yuliia V Lysanets, Ivanna V Znamenska, Inesa V Rozhenko, Nataliia M Nikolaieva
INTRODUCTION: The present paper examines the linguistic status of terminological collocations in medical Latin and English, discusses the most productive term-formation models and ways of Latin-English translation. AIM: The authors aim to provide the comparative analysis of Latin and English terminological collocations and suggest their classification in terms of the idiomaticity level and semantic valency. MATERIALS AND METHODS: The research is based on the corpus of terminological collocations in Latin and English medical discourse using structural, etymological, typological, comparative methods, as well as the method of semantic analysis and conceptual metaphor theory...
2017: Wiadomości Lekarskie: Organ Polskiego Towarzystwa Lekarskiego
https://www.readbyqxmd.com/read/28343203/developing-the-professional-competence-of-future-doctors-in-the-instructional-setting-of-higher-medical-educational-institutions
#2
Halyna Yu Morokhovets, Yuliia V Lysanets
INTRODUCTION: The main objectives of higher medical education is the continuous professional improvement of physicians to meet the needs dictated by the modern world both at undergraduate and postgraduate levels. In this respect, the system of higher medical education has undergone certain changes - from determining the range of professional competences to the adoption of new standards of education in medicine. AIM: The article aims to analyze the parameters of doctor's professionalism in the context of competence-based approach and to develop practical recommendations for the improvement of instruction techniques...
2017: Wiadomości Lekarskie: Organ Polskiego Towarzystwa Lekarskiego
https://www.readbyqxmd.com/read/28343000/evidence-for-similar-patterns-of-neural-activity-elicted-by-picture-and-word-based-representations-of-natural-scenes
#3
Manoj Kumar, Kara D Federmeier, Li Fei-Fei, Diane M Beck
A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g...
March 22, 2017: NeuroImage
https://www.readbyqxmd.com/read/28339791/bridg-a-domain-information-model-for-translational-and-clinical-protocol-driven-research
#4
Lauren B Becnel, Smita Hastak, Wendy Ver Hoef, Robert P Milius, MaryAnn Slack, Diane Wold, Michael L Glickman, Boris Brodsky, Charles Jaffe, Rebecca Kush, Edward Helton
Background: It is critical to integrate and analyze data from biological, translational, and clinical studies with data from health systems; however, electronic artifacts are stored in thousands of disparate systems that are often unable to readily exchange data. Objective: To facilitate meaningful data exchange, a model that presents a common understanding of biomedical research concepts and their relationships with health care semantics is required. The Biomedical Research Integrated Domain Group (BRIDG) domain information model fulfills this need...
February 26, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28339747/deep-learning-for-pharmacovigilance-recurrent-neural-network-architectures-for-labeling-adverse-drug-reactions-in-twitter-posts
#5
Anne Cocos, Alexander G Fiks, Aaron J Masino
Objective: Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is to develop a scalable, deep-learning approach that exceeds state-of-the-art ADR detection performance in social media...
February 22, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28339684/embedding-nursing-interventions-into-the-world-health-organization-s-international-classification-of-health-interventions-ichi
#6
Nicola Fortune, Nicholas R Hardiker, Gillian Strudwick
Objective: : The International Classification of Health Interventions, currently being developed, seeks to span all sectors of the health system. Our objective was to test the draft classification's coverage of interventions commonly delivered by nurses, and propose changes to improve the utility and reliability of the classification for aggregating and analyzing data on nursing interventions. Materials and methods: : A 2-phase content mapping method was used: (1) three coders independently applied the classification to a dataset comprising 100 high-frequency nursing interventions; (2) the coders reached consensus for each intervention and identified reasons for initial discrepancies...
February 11, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28339486/a-top-down-manner-based-dcnn-architecture-for-semantic-image-segmentation
#7
Kai Qiao, Jian Chen, Linyuan Wang, Lei Zeng, Bin Yan
Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs) have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentation task requires not only recognition but also visual attention capability. In the study, superpixels containing visual attention information are introduced in a top-down manner, and an extensible architecture is proposed to improve the segmentation results of current DCNN-based methods...
2017: PloS One
https://www.readbyqxmd.com/read/28339468/pbmda-a-novel-and-effective-path-based-computational-model-for-mirna-disease-association-prediction
#8
Zhu-Hong You, Zhi-An Huang, Zexuan Zhu, Gui-Ying Yan, Zheng-Wei Li, Zhenkun Wen, Xing Chen
In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases...
March 24, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28338944/salience-network-engagement-with-the-detection-of-morally-laden-information
#9
Gunes Sevinc, I Hakan Gurvit, R Nathan Spreng
Moral cognition is associated with activation of the default network, regions implicated in mentalizing about one's own actions or the intentions of others. Yet little is known about the initial detection of moral information. We examined the neural correlates of moral processing during a narrative completion task, which included an implicit moral salience manipulation. During fMRI scanning, participants read a brief vignette and selected the most semantically congruent sentence from two options to complete the narrative...
March 9, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28338829/seeing-is-not-stereotyping-the-functional-independence-of-categorization-and-stereotype-activation
#10
Tiffany A Ito, Silvia Tomelleri
Social categorization has been viewed as necessarily resulting in stereotyping, yet extant research suggests the two processes are differentially sensitive to task manipulations. Here we simultaneously test the degree to which race perception and stereotyping are conditionally automatic. Participants performed a sequential priming task while either explicitly attending to the race of face primes or directing attention away from their semantic nature. We find a dissociation between the perceptual encoding of race and subsequent activation of associated stereotypes, with race perception occurring in both task conditions, but implicit stereotyping occurring only when attention is directed to the race of the face primes...
February 23, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28338350/consensus-driven-development-of-a-terminology-for-biobanking-the-duke-experience
#11
Helena Ellis, Mary-Beth Joshi, Aenoch J Lynn, Anita Walden
Biobanking at Duke University has existed for decades and has grown over time in silos and based on specialized needs, as is true with most biomedical research centers. These silos developed informatics systems to support their own individual requirements, with no regard for semantic or syntactic interoperability. Duke undertook an initiative to implement an enterprise-wide biobanking information system to serve its many diverse biobanking entities. A significant part of this initiative was the development of a common terminology for use in the commercial software platform...
March 24, 2017: Biopreservation and Biobanking
https://www.readbyqxmd.com/read/28337410/damage-to-white-matter-bottlenecks-contributes-to-language-impairments-after-left-hemispheric-stroke
#12
Joseph C Griffis, Rodolphe Nenert, Jane B Allendorfer, Jerzy P Szaflarski
Damage to the white matter underlying the left posterior temporal lobe leads to deficits in multiple language functions. The posterior temporal white matter may correspond to a bottleneck where both dorsal and ventral language pathways are vulnerable to simultaneous damage. Damage to a second putative white matter bottleneck in the left deep prefrontal white matter involving projections associated with ventral language pathways and thalamo-cortical projections has recently been proposed as a source of semantic deficits after stroke...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28337216/smart-data-where-the-big-data-meets-the-semantics
#13
EDITORIAL
Trong H Duong, Hong Q Nguyen, Geun S Jo
No abstract text is available yet for this article.
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28336965/exploring-approaches-for-detecting-protein-functional-similarity-within-an-orthology-based-framework
#14
Christian X Weichenberger, Antonia Palermo, Peter P Pramstaller, Francisco S Domingues
Protein functional similarity based on gene ontology (GO) annotations serves as a powerful tool when comparing proteins on a functional level in applications such as protein-protein interaction prediction, gene prioritization, and disease gene discovery. Functional similarity (FS) is usually quantified by combining the GO hierarchy with an annotation corpus that links genes and gene products to GO terms. One large group of algorithms involves calculation of GO term semantic similarity (SS) between all the terms annotating the two proteins, followed by a second step, described as "mixing strategy", which involves combining the SS values to yield the final FS value...
March 23, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28336477/a-novel-semantic-representation-for-eligibility-criteria-in-clinical-trials
#15
Efthymios Chondrogiannis, Vassiliki Andronikou, Anastasios Tagaris, Efstathios Karanastasis, Theodora Varvarigou, Masatsugu Tsuji
Eligibility Criteria (EC) comprise an important part of a clinical study, being determinant of its cost, duration and overall success. Their formal, computer-processable description can significantly improve clinical trial design and conduction by enabling their intelligent processing, replicability and linkability with other data. For EC representation purposes, related standards were investigated, along with published literature. Moreover, a considerable number of clinicaltrials.gov studies was analyzed in collaboration with clinical experts for the determination and classification of parameters of clinical research importance...
March 21, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28335555/activity-recognition-and-semantic-description-for-indoor-mobile-localization
#16
Sheng Guo, Hanjiang Xiong, Xianwei Zheng, Yan Zhou
As a result of the rapid development of smartphone-based indoor localization technology, location-based services in indoor spaces have become a topic of interest. However, to date, the rich data resulting from indoor localization and navigation applications have not been fully exploited, which is significant for trajectory correction and advanced indoor map information extraction. In this paper, an integrated location acquisition method utilizing activity recognition and semantic information extraction is proposed for indoor mobile localization...
March 21, 2017: Sensors
https://www.readbyqxmd.com/read/28335498/on-the-prediction-of-flickr-image-popularity-by-analyzing-heterogeneous-social-sensory-data
#17
Samah Aloufi, Shiai Zhu, Abdulmotaleb El Saddik
The increase in the popularity of social media has shattered the gap between the physical and virtual worlds. The content generated by people or social sensors on social media provides information about users and their living surroundings, which allows us to access a user's preferences, opinions, and interactions. This provides an opportunity for us to understand human behavior and enhance the services provided for both the real and virtual worlds. In this paper, we will focus on the popularity prediction of social images on Flickr, a popular social photo-sharing site, and promote the research on utilizing social sensory data in the context of assisting people to improve their life on the Web...
March 19, 2017: Sensors
https://www.readbyqxmd.com/read/28335486/implicit-regularization-for-reconstructing-3d-building-rooftop-models-using-airborne-lidar-data
#18
Jaewook Jung, Yoonseok Jwa, Gunho Sohn
With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task...
March 19, 2017: Sensors
https://www.readbyqxmd.com/read/28335431/building-a-relationship-between-robot-characteristics-and-teleoperation-user-interfaces
#19
Michael Mortimer, Ben Horan, Mehdi Seyedmahmoudian
The Robot Operating System (ROS) provides roboticists with a standardized and distributed framework for real-time communication between robotic systems using a microkernel environment. This paper looks at how ROS metadata, Unified Robot Description Format (URDF), Semantic Robot Description Format (SRDF), and its message description language, can be used to identify key robot characteristics to inform User Interface (UI) design for the teleoperation of heterogeneous robot teams. Logical relationships between UI components and robot characteristics are defined by a set of relationship rules created using relevant and available information including developer expertise and ROS metadata...
March 14, 2017: Sensors
https://www.readbyqxmd.com/read/28333637/multi-scale-multi-feature-context-modeling-for-scene-recognition-in-the-semantic-manifold
#20
Xinhang Song, Shuqiang Jiang, Luis Herranz
Before the big data era, scene recognition was often approached with two-step inference using localized intermediate representations (objects, topics, etc). One of such approaches is the semantic manifold (SM), in which patches and images are modeled as points in a semantic probability simplex. Patch models are learned resorting to weak supervision via image labels, which leads to the problem of scene categories co-occurring in this semantic space. Fortunately, each category has its own cooccurrence patterns that are consistent across the images in that category...
March 22, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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