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https://www.readbyqxmd.com/read/29151135/classification-of-g-protein-coupled-receptors-based-on-a-rich-generation-of-convolutional-neural-network-n-gram-transformation-and-multiple-sequence-alignments
#1
Man Li, Cheng Ling, Qi Xu, Jingyang Gao
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique...
November 18, 2017: Amino Acids
https://www.readbyqxmd.com/read/29149241/statistical-learning-in-specific-language-impairment-a-meta-analysis
#2
Imme Lammertink, Paul Boersma, Frank Wijnen, Judith Rispens
Purpose: The current meta-analysis provides a quantitative overview of published and unpublished studies on statistical learning in the auditory verbal domain in people with and without specific language impairment (SLI). The database used for the meta-analysis is accessible online and open to updates (Community-Augmented Meta-Analysis), which facilitates the accumulation and evaluation of previous and future studies on statistical learning in this domain. Method: A systematic literature search identified 10 unique experiments examining auditory verbal statistical learning in 213 participants with SLI and 363 without SLI, aged between 6 and 19 years...
November 17, 2017: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/29149217/per-service-supervised-learning-for-identifying-desired-wot-apps-from-user-requests-in-natural-language
#3
Young Yoon
Web of Things (WoT) platforms are growing fast so as the needs for composing WoT apps more easily and efficiently. We have recently commenced the campaign to develop an interface where users can issue requests for WoT apps entirely in natural language. This requires an effort to build a system that can learn to identify relevant WoT functions that fulfill user's requests. In our preceding work, we trained a supervised learning system with thousands of publicly-available IFTTT app recipes based on conditional random fields (CRF)...
2017: PloS One
https://www.readbyqxmd.com/read/29146464/language-control-mechanisms-differ-for-native-languages-neuromagnetic-evidence-from-trilingual-language-switching
#4
Suzanne C A Hut, Päivi Helenius, Alina Leminen, Jyrki P Mäkelä, Minna Lehtonen
How does the brain process and control languages that are learned at a different age, when proficiency in all these languages is high? Early acquired strong languages are likely to have higher baseline activation levels than later learned less-dominant languages. However, it is still largely unknown how the activation levels of these different languages are controlled, and how interference from an irrelevant language is prevented. In this magnetoencephalography (MEG) study on language switching during auditory perception, early Finnish-Swedish bilinguals (N=18) who mastered English with high proficiency after childhood were presented with spoken words in each of the three languages, while performing a simple semantic categorisation task...
November 13, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/29145671/distinct-cerebellar-contributions-to-cognitive-perceptual-dynamics-during-natural-viewing
#5
Vinh Thai Nguyen, Saurabh Sonkusare, Jane Stadler, Xintao Hu, Michael Breakspear, Christine Cong Guo
The crucial role of the cerebellum in motor learning and coordination is very well known. Considerable interest has recently shifted toward its contribution to nonmotor tasks, such as working memory, emotion, and language. However, the cognitive role and functional subdivisions of the cerebellum, particularly in dynamic, ecologically realistic contexts, are not yet established. By analyzing functional neuroimaging data acquired while participants viewed a short dramatic movie, we found that posterior and inferior cerebellar regions are reliably engaged in dynamic perceptual and affective processes with no explicit motor component...
December 1, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/29143061/the-origins-of-verb-learning-preverbal-and-postverbal-infants-learning-of-word-action-relations
#6
Lakshmi Gogate, Madhavilatha Maganti
Purpose: This experiment examined English- or Spanish-learning preverbal (8-9 months, n = 32) and postverbal (12-14 months, n = 40) infants' learning of word-action pairings prior to and after the transition to verb comprehension and its relation to naturally learned vocabulary. Method: Infants of both verbal levels were first habituated to 2 dynamic video displays of novel word-action pairings, the words /wem/ or /bæf/, spoken synchronously with an adult shaking or looming an object, and tested with interchanged (switched) versus same word-action pairings...
November 15, 2017: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/29142808/analyzing-microtomography-data-with-python-and-the-scikit-image-library
#7
Emmanuelle Gouillart, Juan Nunez-Iglesias, Stéfan van der Walt
The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements...
2017: Advanced Structural and Chemical Imaging
https://www.readbyqxmd.com/read/29140189/predicting-the-sources-of-impaired-wh-question-comprehension-in-non-fluent-aphasia-a-cross-linguistic-machine-learning-study-on-turkish-and-german
#8
Seçkin Arslan, Eren Gür, Claudia Felser
This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-pointing tasks. Findings from our experiments show that the Turkish IWA responded more accurately to both object who and object which questions than to subject questions, while the German IWA performed better for subject which questions than in all other conditions...
November 15, 2017: Cognitive Neuropsychology
https://www.readbyqxmd.com/read/29139649/construction-of-the-questionnaire-on-foreign-language-learning-strategies-in-specific-croatian-context
#9
Nikolina Božinović, Joško Sindik
Learning strategies are special thoughts or behaviours that individuals use to understand, learn or retain new information, according to the point of view of O’Malley & Chamot. The other view, promoted by Oxford, believes learning strategies are specific actions taken by the learner to make learning easier, faster, more enjoyable, and more transferrable to new situations of language learning and use. The use of appropriate strategies ensures greater success in language learning. The aim of the research was to establish metric characteristics of the Questionnaire on learning strategies created by the author, in line with the template of the original SILL questionnaire (Strategy Inventory for Language Learning)...
March 2017: Collegium Antropologicum
https://www.readbyqxmd.com/read/29137720/improving-surgical-residents-communication-in-disclosing-complications-a-qualitative-analysis-of-simulated-physician-and-patient-surrogate-conversations
#10
Carolina Fernandez Branson, Jeffrey G Chipman
BACKGROUND: In this study, we explore surgical resident communication with simulated patient surrogates (SPs), in an Objective Structured Clinical Examination (OSCE). METHODS: We use discourse analysis (DA), a qualitative approach to analyzing language, to evaluate our residents' interactions with simulated patient surrogates. After identifying problematic communication patterns, we apply communication theory to discuss our findings and provide suggestions for improvement...
November 7, 2017: American Journal of Surgery
https://www.readbyqxmd.com/read/29135750/student-and-educator-experiences-of-maternal-child-simulation-based-learning-a-systematic-review-of-qualitative-evidence
#11
Karen MacKinnon, Lenora Marcellus, Julie Rivers, Carol Gordon, Maureen Ryan, Diane Butcher
BACKGROUND: Although maternal-child care is a pillar of primary health care, there is a global shortage of maternal-child health care providers. Nurse educators experience difficulties providing undergraduate students with maternal-child learning experiences for a number of reasons. Simulation has the potential to complement learning in clinical and classroom settings. Although systematic reviews of simulation are available, no systematic reviews of qualitative evidence related to maternal-child simulation-based learning (SBL) for undergraduate nursing students and/or educators have been located...
November 2017: JBI Database of Systematic Reviews and Implementation Reports
https://www.readbyqxmd.com/read/29135365/deep-learning-to-classify-radiology-free-text-reports
#12
Matthew C Chen, Robyn L Ball, Lingyao Yang, Nathaniel Moradzadeh, Brian E Chapman, David B Larson, Curtis P Langlotz, Timothy J Amrhein, Matthew P Lungren
Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE...
November 13, 2017: Radiology
https://www.readbyqxmd.com/read/29131888/exemplar-variability-facilitates-retention-of-word-learning-by-children-with-specific-language-impairment
#13
Jessica M Aguilar, Elena Plante, Michelle Sandoval
Purpose: Variability in the input plays an important role in language learning. The current study examined the role of object variability for new word learning by preschoolers with specific language impairment (SLI). Method: Eighteen 4- and 5-year-old children with SLI were taught 8 new words in 3 short activities over the course of 3 sessions. Half of the children saw 3 identical objects corresponding to each new word during training (No Variability group); the other half of the children saw 3 different objects corresponding to each new word during training (High Variability group)...
November 13, 2017: Language, Speech, and Hearing Services in Schools
https://www.readbyqxmd.com/read/29131760/deep-learning-a-primer-for-radiologists
#14
Gabriel Chartrand, Phillip M Cheng, Eugene Vorontsov, Michal Drozdzal, Simon Turcotte, Christopher J Pal, Samuel Kadoury, An Tang
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance...
November 2017: Radiographics: a Review Publication of the Radiological Society of North America, Inc
https://www.readbyqxmd.com/read/29131709/an-exploration-of-motor-learning-concepts-relevant-to-use-of-speech-generating-devices
#15
Elena Dukhovny, Jennifer J Thistle
For individuals who rely on speech-generating devices (SGDs) to complement and substitute for spoken language, speed and accuracy of access to the device are paramount for effective communication. There is some evidence that application of motor memory principles may improve effectiveness of SGD-based communication. This article reviews motor learning models and principles, including learning stages, types of practice and environmental factors that affect learning, and highlights the potential applications of these principles in dynamic display SGD design, intervention and research...
November 13, 2017: Assistive Technology: the Official Journal of RESNA
https://www.readbyqxmd.com/read/29131368/models-of-chinese-reading-review-and-analysis
#16
Erik D Reichle, Lili Yu
Our understanding of the cognitive processes involved in reading has been advanced by computational models that simulate those processes (e.g., see Reichle, 2015). Unfortunately, most of these models have been developed to explain the reading of English and other alphabetic languages, with relatively fewer efforts to examine whether or not the assumptions of these models also explain what has been learned from other languages and, in particular, non-alphabetic writing systems like Chinese (e.g., see Li, Zang, Liversedge, & Pollatsek, 2015)...
November 13, 2017: Cognitive Science
https://www.readbyqxmd.com/read/29129731/individual-differences-in-visual-science-what-can-be-learned-and-what-is-good-experimental-practice
#17
John D Mollon, Jenny M Bosten, David H Peterzell, Michael A Webster
We all pass out our lives in private perceptual worlds. The differences in our sensory and perceptual experiences often go unnoticed until there emerges a variation (such as 'The Dress') that is large enough to generate different descriptions in the coarse coinage of our shared language. In this essay, we illustrate how individual differences contribute to a richer understanding of visual perception, but we also indicate some potential pitfalls that face the investigator who ventures into the field.
November 9, 2017: Vision Research
https://www.readbyqxmd.com/read/29128736/optimal-practice-conditions-enhance-the-benefits-of-gradually-increasing-error-opportunities-on-retention-of-a-stepping-sequence-task
#18
Danielle Levac, Kate Driscoll, Jessica Galvez, Kathleen Mercado, Lindsey O'Neil
INTRODUCTION: Physical therapists should implement practice conditions that promote motor skill learning after neurological injury. Errorful and errorless practice conditions are effective for different populations and tasks. Errorful learning provides opportunities for learners to make task-relevant choices. Enhancing learner autonomy through choice opportunities is a key component of the Optimizing Performance through Intrinsic Motivation and Attention for Learning (OPTIMAL) theory of motor learning...
November 9, 2017: Human Movement Science
https://www.readbyqxmd.com/read/29128578/electrical-brain-stimulation-tes-improves-learning-more-than-performance-a-meta-analysis
#19
REVIEW
Bianca A Simonsmeier, Roland H Grabner, Julia Hein, Ugne Krenz, Michael Schneider
Researchers have recently started evaluating whether stimulating the brain noninvasively with a weak and painless electrical current (transcranial Electrical Stimulation, tES) enhances physiological and cognitive processes. Some studies found that tES has weak but positive effects on brain physiology, cognition, or assessment performance, which have attracted massive public interest. We present the first meta-analytic test of the hypothesis that tES in a learning phase is more effective than tES in an assessment phase...
November 8, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/29126825/artificial-intelligence-in-medical-practice-the-question-to-the-answer
#20
REVIEW
D Douglas Miller, Eric W Brown
Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society - forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence...
November 7, 2017: American Journal of Medicine
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