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Retrieval-based learning

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https://www.readbyqxmd.com/read/28531339/limtox-a-web-tool-for-applied-text-mining-of-adverse-event-and-toxicity-associations-of-compounds-drugs-and-genes
#1
Andres Cañada, Salvador Capella-Gutierrez, Obdulia Rabal, Julen Oyarzabal, Alfonso Valencia, Martin Krallinger
A considerable effort has been devoted to retrieve systematically information for genes and proteins as well as relationships between them. Despite the importance of chemical compounds and drugs as a central bio-entity in pharmacological and biological research, only a limited number of freely available chemical text-mining/search engine technologies are currently accessible. Here we present LimTox (Literature Mining for Toxicology), a web-based online biomedical search tool with special focus on adverse hepatobiliary reactions...
May 22, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28511771/multiple-priming-instances-increase-the-impact-of-practice-based-but-not-verbal-code-based-stimulus-response-associations
#2
Christina U Pfeuffer, Karolina Moutsopoulou, Florian Waszak, Andrea Kiesel
Stimulus-response (S-R) associations, the basis of learning and behavioral automaticity, are formed by the (repeated) co-occurrence of stimuli and responses and render stimuli able to automatically trigger associated responses. The strength and behavioral impact of these S-R associations increases with the number of priming instances (i.e., practice). Here we investigated whether multiple priming instances of a special form of instruction, verbal coding, also lead to the formation of stronger S-R associations in comparison to a single instance of priming...
May 13, 2017: Acta Psychologica
https://www.readbyqxmd.com/read/28510210/brain-connectivity-during-encoding-and-retrieval-of-spatial-information-individual-differences-in-navigation-skills
#3
Greeshma Sharma, Klaus Gramann, Sushil Chandra, Vijander Singh, Alok Prakash Mittal
Emerging evidence suggests that the variations in the ability to navigate through any real or virtual environment are accompanied by distinct underlying cortical activations in multiple regions of the brain. These activations may appear due to the use of different frame of reference (FOR) for representing an environment. The present study investigated the brain dynamics in the good and bad navigators using Graph Theoretical analysis applied to low-density electroencephalography (EEG) data. Individual navigation skills were rated according to the performance in a virtual reality (VR)-based navigation task and the effect of navigator's proclivity towards a particular FOR on the navigation performance was explored...
May 16, 2017: Brain Informatics
https://www.readbyqxmd.com/read/28500004/generic-content-based-retrieval-of-marker-based-motion-capture-data
#4
Na Lv, Zifei Jiang, Yan Huang, Xiangxu Meng, Gopi M, Jingliang Peng
In this work, we propose an original scheme for generic content-based retrieval of marker-based motion capture data. It works on motion capture data of arbitrary subject types and arbitrary marker attachment and labelling conventions. Specifically, we propose a novel motion signature to statistically describe both the high-level and the low-level morphological and kinematic characteristics of a motion capture sequence, and conduct the content-based retrieval by computing and ordering the motion signature distance between the query and every item in the database...
May 9, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28498063/preliminary-evaluation-of-a-novel-rigid-bronchoscopy-simulator
#5
Grace E Hsiung, Ben Schwab, Ellen K O'Brien, Colin D Gause, Ferdynand Hebal, Katherine A Barsness, Deborah M Rooney
PURPOSE: Emergent retrieval of airway foreign bodies (AFBs) in children remains a priority skill set for pediatric surgeons. In the setting of low procedural volume, simulation-based education with deliberate practice is essential to ensure trainees reach expected surgical competency. The purposes of this work were to (1) create a realistic rigid bronchoscopy for AFB retrieval simulation model and (2) to evaluate preliminary validity evidence of a novel simulator for the use of training and assessing pediatric surgical trainees' rigid bronchoscopy skills...
May 12, 2017: Journal of Laparoendoscopic & Advanced Surgical Techniques. Part A
https://www.readbyqxmd.com/read/28476106/geminivirus-data-warehouse-a-database-enriched-with-machine-learning-approaches
#6
Jose Cleydson F Silva, Thales F M Carvalho, Marcos F Basso, Michihito Deguchi, Welison A Pereira, Roberto R Sobrinho, Pedro M P Vidigal, Otávio J B Brustolini, Fabyano F Silva, Maximiller Dal-Bianco, Renildes L F Fontes, Anésia A Santos, Francisco Murilo Zerbini, Fabio R Cerqueira, Elizabeth P B Fontes
BACKGROUND: The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases...
May 5, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28475047/retrieval-of-sentence-sequences-for-an-image-stream-via-coherence-recurrent-convolutional-networks
#7
Cesc Park, Youngjin Kim, Gunhee Kim
We propose an approach for retrieving a sequence of natural sentences for an image stream. Since general users often take a series of pictures on their experiences, much online visual information exists in the form of image streams, for which it would better take into consideration of the whole image stream to produce natural language descriptions. While almost all previous studies have dealt with the relation between a single image and a single natural sentence, our work extends both input and output dimension to a sequence of images and a sequence of sentences...
May 2, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28472272/modlamp-python-for-antimicrobial-peptides
#8
Alex T Müller, Gisela Gabernet, Jan A Hiss, Gisbert Schneider
Summary: We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification, and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled data sets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra...
May 4, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28463622/initial-experience-with-a-robotically-operated-video-optical-telescopic-microscope-in-cranial-neurosurgery-feasibility-safety-and-clinical-applications
#9
Lior Gonen, Srikant S Chakravarthi, Alejandro Monroy-Sosa, Juanita M Celix, Nathaniel Kojis, Maharaj Singh, Jonathan Jennings, Melanie B Fukui, Richard A Rovin, Amin B Kassam
OBJECTIVE The move toward better, more effective optical visualization in the field of neurosurgery has been a focus of technological innovation. In this study, the authors' objectives are to describe the feasibility and safety of a new robotic optical platform, namely, the robotically operated video optical telescopic-microscope (ROVOT-m), in cranial microsurgical applications. METHODS A prospective database comprising patients who underwent a cranial procedure between April 2015 and September 2016 was queried, and the first 200 patients who met the inclusion criteria were selected as the cohort for a retrospective chart review...
May 2017: Neurosurgical Focus
https://www.readbyqxmd.com/read/28453576/a-novel-framework-for-the-identification-of-drug-target-proteins-combining-stacked-auto-encoders-with-a-biased-support-vector-machine
#10
Qi Wang, YangHe Feng, JinCai Huang, TengJiao Wang, GuangQuan Cheng
The identification of drug target proteins (IDTP) plays a critical role in biometrics. The aim of this study was to retrieve potential drug target proteins (DTPs) from a collected protein dataset, which represents an overwhelming task of great significance. Previously reported methodologies for this task generally employ protein-protein interactive networks but neglect informative biochemical attributes. We formulated a novel framework utilizing biochemical attributes to address this problem. In the framework, a biased support vector machine (BSVM) was combined with the deep embedded representation extracted using a deep learning model, stacked auto-encoders (SAEs)...
2017: PloS One
https://www.readbyqxmd.com/read/28452688/ethno-cultural-preferences-in-receipt-of-heart-health-information
#11
Pavneet Singh, K Alix Hayden, Twyla Ens, Nadia Khan, Hude Quan, Deanna Plested, Shane Sinclair, Kathryn M King-Shier
OBJECTIVE: We attempted to understand how people of South Asian and Chinese descent prefer to receive health information. METHODS: To achieve this end we conducted a search of academic and grey literature articles published between 1946 and 2016. To be included, articles had to be focused South Asian and Chinese specific ethno-culturally-based preferences of receiving health information. RESULTS: A total of 3478 abstracts were retrieved, of which, 27 articles met the inclusion criteria...
March 1, 2017: American Journal of Health Behavior
https://www.readbyqxmd.com/read/28449114/neuro-symbolic-representation-learning-on-biological-knowledge-graphs
#12
Mona Alshahrani, Mohammed Asif Khan, Omar Maddouri, Akira R Kinjo, Núria Queralt-Rosinach, Robert Hoehndorf
Motivation: Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs...
April 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28446872/a-neurocomputational-model-of-goal-directed-navigation-in-insect-inspired-artificial-agents
#13
Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta
Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28444634/watching-diagnoses-develop-eye-movements-reveal-symptom-processing-during-diagnostic-reasoning
#14
Agnes Scholz, Josef F Krems, Georg Jahn
Finding a probable explanation for observed symptoms is a highly complex task that draws on information retrieval from memory. Recent research suggests that observed symptoms are interpreted in a way that maximizes coherence for a single likely explanation. This becomes particularly clear if symptom sequences support more than one explanation. However, there are no existing process data available that allow coherence maximization to be traced in ambiguous diagnostic situations, where critical information has to be retrieved from memory...
April 25, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/28436904/user-preference-based-dual-memory-neural-model-with-memory-consolidation-approach
#15
Jauwairia Nasir, Yong-Ho Yoo, Deok-Hwa Kim, Jong-Hwan Kim
Memory modeling has been a popular topic of research for improving the performance of autonomous agents in cognition related problems. Apart from learning distinct experiences correctly, significant or recurring experiences are expected to be learned better and be retrieved easier. In order to achieve this objective, this paper proposes a user preference-based dual-memory adaptive resonance theory network model, which makes use of a user preference to encode memories with various strengths and to learn and forget at various rates...
April 24, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28435123/is-having-similar-eye-movement-patterns-during-face-learning-and-recognition-beneficial-for-recognition-performance-evidence-from-hidden-markov-modeling
#16
Tim Chuk, Antoni B Chan, Janet Hsiao
The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition...
April 20, 2017: Vision Research
https://www.readbyqxmd.com/read/28423792/acronym-disambiguation-in-spanish-electronic-health-narratives-using-machine-learning-techniques
#17
Ignacio Rubio-López, Roberto Costumero, Héctor Ambit, Consuelo Gonzalo-Martín, Ernestina Menasalvas, Alejandro Rodríguez González
Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical narratives (unstructured data) making it possible to perform context-based searches. Current approaches to process the unstructured texts in EHRs are based in applying text mining or natural language processing (NLP) techniques over the data. In particular Named Entity Recognition (NER) is of paramount importance to retrieve specific biomedical concepts from the text providing the semantic type of the concept retrieved...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28422613/the-impact-of-prospective-telemedicine-implementation-in-the-management-of-childhood-acute-lymphoblastic-leukemia-in-recife-brazil
#18
Francisco Pedrosa, Faisal Shaikh, Gaston Rivera, Raul Ribeiro, Ibrahim Qaddoumi
BACKGROUND: A gap in childhood cancer outcomes remains between developed and developing countries. Persistence of this gap may be caused by financial, social, or educational disparities. Twinning and distance learning initiatives may improve such disparities. Integrating telemedicine into pediatric oncology twinning programs enhances education and facilitates patient-centered capacity building. MATERIALS AND METHODS: We performed an analysis of Web-based meetings held from August 2005 through July 2009 between the International Outreach Program at St...
April 19, 2017: Telemedicine Journal and E-health: the Official Journal of the American Telemedicine Association
https://www.readbyqxmd.com/read/28416633/intrusions-in-episodic-memory-reconsolidation-or-interference
#19
Angela Klingmüller, Jeremy B Caplan, Tobias Sommer
It would be profoundly important if reconsolidation research in animals and other memory domains generalized to human episodic memory. A 3-d-list-discrimination procedure, based on free recall of objects, with a contextual reminder cue (the testing room), has been thought to demonstrate reconsolidation of human episodic memory (as noted in a previous study). Our goal was to replicate the central result, a high intrusion rate during recall of the target list, and evaluate the reconsolidation account relative to an alternative account, based on state-dependent learning and interference...
May 2017: Learning & Memory
https://www.readbyqxmd.com/read/28412964/mesh-now-automatic-mesh-indexing-at-pubmed-scale-via-learning-to-rank
#20
Yuqing Mao, Zhiyong Lu
BACKGROUND: MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging...
April 17, 2017: Journal of Biomedical Semantics
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