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https://www.readbyqxmd.com/read/29774229/web-pages-what-can-you-see-in-a-single-fixation
#1
Ali Jahanian, Shaiyan Keshvari, Ruth Rosenholtz
Research in human vision suggests that in a single fixation, humans can extract a significant amount of information from a natural scene, e.g. the semantic category, spatial layout, and object identities. This ability is useful, for example, for quickly determining location, navigating around obstacles, detecting threats, and guiding eye movements to gather more information. In this paper, we ask a new question: What can we see at a glance at a web page - an artificial yet complex "real world" stimulus? Is it possible to notice the type of website, or where the relevant elements are, with only a glimpse? We find that observers, fixating at the center of a web page shown for only 120 milliseconds, are well above chance at classifying the page into one of ten categories...
2018: Cognitive Research: Principles and Implications
https://www.readbyqxmd.com/read/29725962/standard-lexicons-coding-systems-and-ontologies-for-interoperability-and-semantic-computation-in-imaging
#2
REVIEW
Kenneth C Wang
Standard clinical terms, codes, and ontologies promote clarity and interoperability. Within radiology, there is a variety of relevant content resources, tools and technologies. These provide the basis for fundamental imaging workflows such as reporting and billing, and also facilitate a range of applications in quality improvement and research. This article reviews the key characteristics of lexicons, coding systems, and ontologies. A number of standards are described, including International Classification of Diseases-10-Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and RadLex...
May 3, 2018: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/29678082/radiation-oncology-terminology-linker-a-step-towards-a-linked-data-knowledge-base
#3
Tim Lustberg, Johan van Soest, Peter Fick, Rianne Fijten, Tim Hendriks, Sander Puts, Andre Dekker
Performing image feature extraction in radiation oncology is often dependent on the organ and tumor delineations provided by clinical staff. These delineation names are free text DICOM metadata fields resulting in undefined information, which requires effort to use in large-scale image feature extraction efforts. In this work we present a scale-able solution to overcome these naming convention challenges with a REST service using Semantic Web technology to convert this information to linked data. As a proof of concept an open source software is used to compute radiation oncology image features...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29678019/combining-the-generic-entity-attribute-value-model-and-terminological-models-into-a-common-ontology-to-enable-data-integration-and-decision-support
#4
Jacques Bouaud, Gilles Guézennec, Brigitte Séroussi
The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29677912/exploring-semantic-data-federation-to-enable-malaria-surveillance-queries
#5
Jon Haël Brenas, Mohammad Sadnan Al Manir, Kate Zinszer, Christopher J O Baker, Arash Shaban-Nejad
Malaria is an infectious disease affecting people across tropical countries. In order to devise efficient interventions, surveillance experts need to be able to answer increasingly complex queries integrating information coming from repositories distributed all over the globe. This, in turn, requires extraordinary coding abilities that cannot be expected from non-technical surveillance experts. In this paper, we present a deployment of Semantic Automated Discovery and Integration (SADI) Web services for the federation and querying of malaria data...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29669592/ggdonto-ontology-as-a-knowledge-base-for-genetic-diseases-and-disorders-of-glycan-metabolism-and-their-causative-genes
#6
Elena Solovieva, Toshihide Shikanai, Noriaki Fujita, Hisashi Narimatsu
BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes...
April 18, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29629236/oc-2-kb-a-software-pipeline-to-build-an-evidence-based-obesity-and-cancer-knowledge-base
#7
Juan Antonio Lossio-Ventura, William Hogan, François Modave, Yi Guo, Zhe He, Amanda Hicks, Jiang Bian
Obesity has been linked to several types of cancer. Access to adequate health information activates people's participation in managing their own health, which ultimately improves their health outcomes. Nevertheless, the existing online information about the relationship between obesity and cancer is heterogeneous and poorly organized. A formal knowledge representation can help better organize and deliver quality health information. Currently, there are several efforts in the biomedical domain to convert unstructured data to structured data and store them in Semantic Web knowledge bases (KB)...
November 2017: Proceedings
https://www.readbyqxmd.com/read/29562918/from-global-action-against-malaria-to-local-issues-state-of-the-art-and-perspectives-of-web-platforms-dealing-with-malaria-information
#8
Dominique Briand, Emmanuel Roux, Jean Christophe Desconnets, Carmen Gervet, Christovam Barcellos
BACKGROUND: Since prehistory to present times and despite a rough combat against it, malaria remains a concern for human beings. While evolutions of science and technology through times allowed for some infectious diseases eradication in the 20th century, malaria resists. OBJECTIVES: This review aims at assessing how Internet and web technologies are used in fighting malaria. Precisely, how do malaria fighting actors profit from these developments, how do they deal with ensuing phenomena, such as the increase of data volume, and did these technologies bring new opportunities for fighting malaria? METHODS: Eleven web platforms linked to spatio-temporal malaria information are reviewed, focusing on data, metadata, web services and categories of users...
March 21, 2018: Malaria Journal
https://www.readbyqxmd.com/read/29533136/the-use-of-the-term-radiosensitivity-through-history-of-radiation-from-clarity-to-confusion
#9
Manon Britel, Michel Bourguignon, Nicolas Foray
PURPOSES: The term 'radiosensitivity' appeared for the first time at the beginning of the 20th century, few years after the discovery of X-rays. Initially used by French and German radiologists, it illustrated the risk of radiation-induced (RI) skin reactions. From the 1950s, 'radiosensitivity' was progressively found to describe other features of RI response such as RI cancers or cataracts. To date, such confusion may raise legal issues and complexify the message addressed to general public...
May 2018: International Journal of Radiation Biology
https://www.readbyqxmd.com/read/29529024/lailaps-qsm-a-restful-api-and-java-library-for-semantic-query-suggestions
#10
Jinbo Chen, Uwe Scholz, Ruonan Zhou, Matthias Lange
In order to access and filter content of life-science databases, full text search is a widely applied query interface. But its high flexibility and intuitiveness is paid for with potentially imprecise and incomplete query results. To reduce this drawback, query assistance systems suggest those combinations of keywords with the highest potential to match most of the relevant data records. Widespread approaches are syntactic query corrections that avoid misspelling and support expansion of words by suffixes and prefixes...
March 2018: PLoS Computational Biology
https://www.readbyqxmd.com/read/29495646/ontology-based-method-for-fault-diagnosis-of-loaders
#11
Feixiang Xu, Xinhui Liu, Wei Chen, Chen Zhou, Bingwei Cao
This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules...
February 28, 2018: Sensors
https://www.readbyqxmd.com/read/29479581/phlegra-graph-analytics-in-pharmacology-over-the-web-of-life-sciences-linked-open-data
#12
Maulik R Kamdar, Mark A Musen
Integrated approaches for pharmacology are required for the mechanism-based predictions of adverse drug reactions that manifest due to concomitant intake of multiple drugs. These approaches require the integration and analysis of biomedical data and knowledge from multiple, heterogeneous sources with varying schemas, entity notations, and formats. To tackle these integrative challenges, the Semantic Web community has published and linked several datasets in the Life Sciences Linked Open Data (LSLOD) cloud using established W3C standards...
April 2017: Proceedings of the International World-Wide Web Conference
https://www.readbyqxmd.com/read/29472179/representation-of-time-relevant-common-data-elements-in-the-cancer-data-standards-repository-statistical-evaluation-of-an-ontological-approach
#13
Henry W Chen, Jingcheng Du, Hsing-Yi Song, Xiangyu Liu, Guoqian Jiang, Cui Tao
BACKGROUND: Today, there is an increasing need to centralize and standardize electronic health data within clinical research as the volume of data continues to balloon. Domain-specific common data elements (CDEs) are emerging as a standard approach to clinical research data capturing and reporting. Recent efforts to standardize clinical study CDEs have been of great benefit in facilitating data integration and data sharing. The importance of the temporal dimension of clinical research studies has been well recognized; however, very few studies have focused on the formal representation of temporal constraints and temporal relationships within clinical research data in the biomedical research community...
February 22, 2018: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29461493/design-and-implementation-of-e-health-system-based-on-semantic-sensor-network-using-ietf-yang
#14
Wenquan Jin, Do Hyeun Kim
Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT) that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention...
February 20, 2018: Sensors
https://www.readbyqxmd.com/read/29409535/dmto-a-realistic-ontology-for-standard-diabetes-mellitus-treatment
#15
Shaker El-Sappagh, Daehan Kwak, Farman Ali, Kyung-Sup Kwak
BACKGROUND: Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic of ontology supports the inference of hidden knowledge. Building a complete, coherent, consistent, interoperable, and sharable ontology is a challenge...
February 6, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29409442/semantic-annotation-of-consumer-health-questions
#16
Halil Kilicoglu, Asma Ben Abacha, Yassine Mrabet, Sonya E Shooshan, Laritza Rodriguez, Kate Masterton, Dina Demner-Fushman
BACKGROUND: Consumers increasingly use online resources for their health information needs. While current search engines can address these needs to some extent, they generally do not take into account that most health information needs are complex and can only fully be expressed in natural language. Consumer health question answering (QA) systems aim to fill this gap. A major challenge in developing consumer health QA systems is extracting relevant semantic content from the natural language questions (question understanding)...
February 6, 2018: BMC Bioinformatics
https://www.readbyqxmd.com/read/29389181/listeners-and-readers-generalize-their-experience-with-word-meanings-across-modalities
#17
Rebecca A Gilbert, Matthew H Davis, M Gareth Gaskell, Jennifer M Rodd
Research has shown that adults' lexical-semantic representations are surprisingly malleable. For instance, the interpretation of ambiguous words (e.g., bark) is influenced by experience such that recently encountered meanings become more readily available (Rodd et al., 2016, 2013). However, the mechanism underlying this word-meaning priming effect remains unclear, and competing accounts make different predictions about the extent to which information about word meanings that is gained within one modality (e...
February 1, 2018: Journal of Experimental Psychology. Learning, Memory, and Cognition
https://www.readbyqxmd.com/read/29387171/semantic-and-syntactic-interoperability-in-online-processing-of-big-earth-observation-data
#18
Martin Sudmanns, Dirk Tiede, Stefan Lang, Andrea Baraldi
The challenge of enabling syntactic and semantic interoperability for comprehensive and reproducible online processing of big Earth observation (EO) data is still unsolved. Supporting both types of interoperability is one of the requirements to efficiently extract valuable information from the large amount of available multi-temporal gridded data sets. The proposed system wraps world models, (semantic interoperability) into OGC Web Processing Services (syntactic interoperability) for semantic online analyses...
2018: International Journal of Digital Earth
https://www.readbyqxmd.com/read/29354810/shapeshop-towards-understanding-deep-learning-representations-via-interactive-experimentation
#19
Fred Hohman, Nathan Hodas, Duen Horng Chau
Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers...
May 2017: Extended Abstracts on Human Factors in Computing Systems
https://www.readbyqxmd.com/read/29351341/labeling-for-big-data-in-radiation-oncology-the-radiation-oncology-structures-ontology
#20
Jean-Emmanuel Bibault, Eric Zapletal, Bastien Rance, Philippe Giraud, Anita Burgun
PURPOSE: Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treatment, since they directly provide medical data on a large scale. In order to gather a significant amount of patients with a high level of clinical details, multicenter studies are necessary. A challenge in creating high quality Big Data studies involving several treatment centers is the lack of semantic interoperability between data sources...
2018: PloS One
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