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https://www.readbyqxmd.com/read/29149223/two-genetic-codes-repetitive-syntax-for-active-non-coding-rnas-non-repetitive-syntax-for-the-dna-archives
#1
Guenther Witzany
Current knowledge of the RNA world indicates 2 different genetic codes being present throughout the living world. In contrast to non-coding RNAs that are built of repetitive nucleotide syntax, the sequences that serve as templates for proteins share-as main characteristics-a non-repetitive syntax. Whereas non-coding RNAs build groups that serve as regulatory tools in nearly all genetic processes, the coding sections represent the evolutionarily successful function of the genetic information storage medium. This indicates that the differences in their syntax structure are coherent with the differences of the functions they represent...
2017: Communicative & Integrative Biology
https://www.readbyqxmd.com/read/29146464/language-control-mechanisms-differ-for-native-languages-neuromagnetic-evidence-from-trilingual-language-switching
#2
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
#3
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/29145178/minor-hemisphere-major-syndromes
#4
Antonio Carota, Julien Bogousslavsky
A right "minor hemisphere" does not exist as the right hemisphere is dominant for awareness (nosognosia), spatial attention, emotional regulation, facial and voice expressions, visual recognition, and topographical orientation. Without the right hemisphere, the world would be flat, deprived of general and spatial attentions, pointing preferentially to the right side of the space, lacking visual experiences and emotions, exhibiting diminished awareness of the self and environment. Clinical-related syndromes of the right hemisphere are unilateral spatial neglect, object and face visual agnosia, the anosognosia for hemiparesis and/or hemianopia, misidentification syndromes, mania, and other obsessions for the food and the body...
2018: Frontiers of Neurology and Neuroscience
https://www.readbyqxmd.com/read/29143250/cliques-and-cavities-in-the-human-connectome
#5
Ann E Sizemore, Chad Giusti, Ari Kahn, Jean M Vettel, Richard F Betzel, Danielle S Bassett
Encoding brain regions and their connections as a network of nodes and edges captures many of the possible paths along which information can be transmitted as humans process and perform complex behaviors. Because cognitive processes involve large, distributed networks of brain areas, principled examinations of multi-node routes within larger connection patterns can offer fundamental insights into the complexities of brain function. Here, we investigate both densely connected groups of nodes that could perform local computations as well as larger patterns of interactions that would allow for parallel processing...
November 16, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29135365/deep-learning-to-classify-radiology-free-text-reports
#6
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/29131760/deep-learning-a-primer-for-radiologists
#7
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/29128736/optimal-practice-conditions-enhance-the-benefits-of-gradually-increasing-error-opportunities-on-retention-of-a-stepping-sequence-task
#8
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/29128453/getting-the-most-out-of-on-line-literature-searches-tips-for-advanced-searches
#9
Dirk M Elston
Thorough and efficient literature searches are important to authors and practicing physicians alike, and modern search engines have many tools to expedite the process. In databases such as PubMed, new logic, or natural language, is set up to answer questions by simply typing them in.
November 8, 2017: Journal of the American Academy of Dermatology
https://www.readbyqxmd.com/read/29126825/artificial-intelligence-in-medical-practice-the-question-to-the-answer
#10
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
https://www.readbyqxmd.com/read/29126650/plasticity-in-the-auditory-system
#11
REVIEW
Dexter R F Irvine
Over the last 30 years a wide range of manipulations of auditory input and experience have been shown to result in plasticity in auditory cortical and subcortical structures. The time course of plasticity ranges from very rapid stimulus-specific adaptation to longer-term changes associated with, for example, partial hearing loss or perceptual learning. Evidence for plasticity as a consequence of these and a range of other manipulations of auditory input and/or its significance is reviewed, with an emphasis on plasticity in adults and in the auditory cortex...
October 31, 2017: Hearing Research
https://www.readbyqxmd.com/read/29121053/adept-a-semantically-enriched-pipeline-for-extracting-adverse-drug-events-from-free-text-electronic-health-records
#12
Ehtesham Iqbal, Robbie Mallah, Daniel Rhodes, Honghan Wu, Alvin Romero, Nynn Chang, Olubanke Dzahini, Chandra Pandey, Matthew Broadbent, Robert Stewart, Richard J B Dobson, Zina M Ibrahim
Adverse drug events (ADEs) are unintended responses to medical treatment. They can greatly affect a patient's quality of life and present a substantial burden on healthcare. Although Electronic health records (EHRs) document a wealth of information relating to ADEs, they are frequently stored in the unstructured or semi-structured free-text narrative requiring Natural Language Processing (NLP) techniques to mine the relevant information. Here we present a rule-based ADE detection and classification pipeline built and tested on a large Psychiatric corpus comprising 264k patients using the de-identified EHRs of four UK-based psychiatric hospitals...
2017: PloS One
https://www.readbyqxmd.com/read/29120251/validity-of-the-flemish-working-alliance-inventory-in-a-dutch-physiotherapy-setting-in-patients-with-shoulder-pain
#13
Yasmaine Karel, Marloes Thoomes-De Graaf, Gwendolijne Scholten-Peeters, Paulo Ferreira, Dimitris Rizopoulos, Bart W Koes, Arianne P Verhagen
BACKGROUND: Working alliance is the interaction between the patient and therapist. It is a crucial part of the physiotherapeutic process. One instrument to measure working alliance is available in Dutch/Flemish language and validated in psychotherapy setting. OBJECTIVE: This study aims to validate the Working Alliance Inventory Short-Form in a Dutch physiotherapy setting. DESIGN: A prospective cohort study in primary-care physiotherapy. METHOD: To validate the Dutch/Flemish version of the working alliance inventory short-form (WAV-12) a RASCH analysis was used...
November 9, 2017: Physiotherapy Theory and Practice
https://www.readbyqxmd.com/read/29112003/measuring-processes-of-care-in-palliative-surgery-a-novel-approach-using-natural-language-processing
#14
Elizabeth J Lilley, Charlotta Lindvall, Keith D Lillemoe, James A Tulsky, Daniel C Wiener, Zara Cooper
: Palliative surgical procedures are often performed for patients with limited survival. Quality measures for processes of care at the end of life are appropriate in palliative surgery, but have not been applied in this patient population. In this paper, the authors propose 4 quality measures for end-of-life care in a palliative surgery, and then demonstrate the utility of natural language processing for implementing these measures.
November 3, 2017: Annals of Surgery
https://www.readbyqxmd.com/read/29109260/natural-language-indicators-of-differential-gene-regulation-in-the-human-immune-system
#15
Matthias R Mehl, Charles L Raison, Thaddeus W W Pace, Jesusa M G Arevalo, Steve W Cole
Adverse social conditions have been linked to a conserved transcriptional response to adversity (CTRA) in circulating leukocytes that may contribute to social gradients in disease. However, the CNS mechanisms involved remain obscure, in part because CTRA gene-expression profiles often track external social-environmental variables more closely than they do self-reported internal affective states such as stress, depression, or anxiety. This study examined the possibility that variations in patterns of natural language use might provide more sensitive indicators of the automatic threat-detection and -response systems that proximally regulate autonomic induction of the CTRA...
November 6, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29109070/artificial-intelligence-learning-semantics-via-external-resources-for-classifying-diagnosis-codes-in-discharge-notes
#16
Chin Lin, Chia-Jung Hsu, Yu-Sheng Lou, Shih-Jen Yeh, Chia-Cheng Lee, Sui-Lung Su, Hsiang-Cheng Chen
BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). OBJECTIVE: Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes...
November 6, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/29104964/a-machine-learning-algorithm-for-identifying-atopic-dermatitis-in-adults-from-electronic-health-records
#17
Erin Gustafson, Jennifer Pacheco, Firas Wehbe, Jonathan Silverberg, William Thompson
The current work aims to identify patients with atopic dermatitis for inclusion in genome-wide association studies (GWAS). Here we describe a machine learning-based phenotype algorithm. Using the electronic health record (EHR), we combined coded information with information extracted from encounter notes as features in a lasso logistic regression. Our algorithm achieves high positive predictive value (PPV) and sensitivity, improving on previous algorithms with low sensitivity. These results demonstrate the utility of natural language processing (NLP) and machine learning for EHR-based phenotyping...
August 2017: IEEE International Conference on Healthcare Informatics IEEE International Conference on Healthcare Informatics
https://www.readbyqxmd.com/read/29098269/neural-indices-of-semantic-processing-in-early-childhood-distinguish-eventual-stuttering-persistence-and-recovery
#18
Kathryn Kreidler, Amanda Hampton Wray, Evan Usler, Christine Weber
Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering (CWS-ePersisted) from those who will recover from stuttering (CWS-eRecovered). Method: Fifty-six 5-year-old children with normal receptive language listened to naturally spoken sentences in a story context...
November 9, 2017: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/29096203/modular-representation-of-layered-neural-networks
#19
Chihiro Watanabe, Kaoru Hiramatsu, Kunio Kashino
Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood...
October 12, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29094990/eye-movements-reveal-persistent-sensitivity-to-sound-symbolism-during-word-learning
#20
Kate Pirog Revill, Laura L Namy, Lynne C Nygaard
Although the relationship between sound and meaning in language is assumed to be largely arbitrary, reliable correspondences between sound and meaning in natural language appear to facilitate word learning. Using a set of independently normed pseudoword and shape stimuli, we examined the real-time effects of sound-to-shape correspondences at initial presentation and throughout an extended learning process resulting in high accuracy. In addition to accuracy and response time (RT) measures, we monitored participants' eye movements to investigate the extent to which visual orienting to objects is influenced by the sound symbolic characteristics of novel labels at initial exposure and throughout learning...
November 2, 2017: Journal of Experimental Psychology. Learning, Memory, and Cognition
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