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Natural language processing

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https://www.readbyqxmd.com/read/28436476/multiplex-lexical-networks-reveal-patterns-in-early-word-acquisition-in-children
#1
Massimo Stella, Nicole M Beckage, Markus Brede
Network models of language have provided a way of linking cognitive processes to language structure. However, current approaches focus only on one linguistic relationship at a time, missing the complex multi-relational nature of language. In this work, we overcome this limitation by modelling the mental lexicon of English-speaking toddlers as a multiplex lexical network, i.e. a multi-layered network where N = 529 words/nodes are connected according to four relationship: (i) free association, (ii) feature sharing, (iii) co-occurrence, and (iv) phonological similarity...
April 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28436261/a-qrt-pcr-and-gene-functional-enrichment-study-focused-on-downregulation-of-mir-141-3p-in-hepatocellular-carcinoma-and-its-clinicopathological-significance
#2
Cui-Zhen Liu, Zhi-Hua Ye, Jie Ma, Rong-Quan He, Hai-Wei Liang, Zhi-Gang Peng, Gang Chen
BACKGROUND: The clinical significance of miR-141-3p in hepatocellular carcinoma has not been verified. Therefore, we conducted this study to examine miR-141-3p expression and its clinical significance in hepatocellular carcinoma and to investigate the functions of its potential targets. METHODS: The Cancer Genome Atlas database and the Gene Expression Omnibus database were used to explore the aberrant expression of miR-141-3p in hepatocellular carcinoma. Furthermore, we assessed the miR-141-3p levels in 95 hepatocellular carcinoma tissues with 95 matched adjacent tissues using real-time quantitative polymerase chain reaction...
January 1, 2017: Technology in Cancer Research & Treatment
https://www.readbyqxmd.com/read/28436212/cross-sectional-and-longitudinal-epidemiological-studies-of-internet-gaming-disorder-a-systematic-review-of-the-literature
#3
REVIEW
Satoko Mihara, Susumu Higuchi
AIM: The diagnostic criteria of Internet Gaming Disorder (IGD) have been included in section III of DSM-5. This study aims to systematically review both cross-sectional and longitudinal epidemiological studies of IGD. METHODS: All publications included in PubMed and PsychINFO up to May 2016 were systematically searched to identify cross-sectional studies on prevalence and longitudinal studies of IGD. In the process of identification, articles in non-English languages, and studies focusing solely on the use of gaming were excluded, and those meeting the methodological requirements set by this review were included...
April 24, 2017: Psychiatry and Clinical Neurosciences
https://www.readbyqxmd.com/read/28428140/automated-annotation-and-classification-of-bi-rads-assessment-from-radiology-reports
#4
Sergio M Castro, Eugene Tseytlin, Olga Medvedeva, Kevin Mitchell, Shyam Visweswaran, Tanja Bekhuis, Rebecca S Jacobson
The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities. The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach...
April 17, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28424636/the-neural-basis-of-speech-perception-through-lipreading-and-manual-cues-evidence-from-deaf-native-users-of-cued-speech
#5
Mario Aparicio, Philippe Peigneux, Brigitte Charlier, Danielle Balériaux, Martin Kavec, Jacqueline Leybaert
We present here the first neuroimaging data for perception of Cued Speech (CS) by deaf adults who are native users of CS. CS is a visual mode of communicating a spoken language through a set of manual cues which accompany lipreading and disambiguate it. With CS, sublexical units of the oral language are conveyed clearly and completely through the visual modality without requiring hearing. The comparison of neural processing of CS in deaf individuals with processing of audiovisual (AV) speech in normally hearing individuals represents a unique opportunity to explore the similarities and differences in neural processing of an oral language delivered in a visuo-manual vs...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28423796/personalized-guideline-based-treatment-recommendations-using-natural-language-processing-techniques
#6
Matthias Becker, Britta Böckmann
Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization. Today, electronic representation of clinical guidelines exists as unstructured text, but is not well-integrated with patient-specific information from electronic health records. Consequently, generic content of the clinical guidelines is accessible, but it is not possible to visualize the position of the patient on the clinical pathway, decision support cannot be provided by personalized guidelines for the next treatment step...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28423792/acronym-disambiguation-in-spanish-electronic-health-narratives-using-machine-learning-techniques
#7
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/28423791/medical-text-classification-using-convolutional-neural-networks
#8
Mark Hughes, Irene Li, Spyros Kotoulas, Toyotaro Suzumura
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health information. Through a detailed evaluation, we demonstrate that our method outperforms several approaches widely used in natural language processing tasks by about 15%.
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28423782/developing-a-manually-annotated-corpus-of-clinical-letters-for-breast-cancer-patients-on-routine-follow-up
#9
Graham Pitson, Patricia Banks, Lawrence Cavedon, Karin Verspoor
This paper introduces the annotation schema and annotation process for a corpus of clinical letters describing the disease course and treatment of oestrogen receptor positive breast cancer patients, after completion of primary surgery and radiotherapy treatment. Concepts related to therapy, clinical signs, and recurrence, as well as relationships linking these, are identified and annotated in 200 letters. This corpus will provide the basis for development of natural language processing tools for automatic extraction of key clinical factors from such letters...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28423780/development-and-evaluation-of-a-case-based-retrieval-service
#10
Emilie Pasche, Marcello Chinali, Julien Gobeill, Patrick Ruch
Identifying similar patients might greatly facilitate the treatment of a given patient, enabling to observe the response and outcome to a particular treatment. Case-based retrieval services dealing with natural language processing are of major importance to deal with the significant amount of unstructured clinical data. In this paper, we present the development and evaluation of a case-based retrieval (CBR) service tested on a collection of Italian pediatric cardiology cases. Cases are indexed and a search engine is proposed...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28419261/challenges-in-adapting-existing-clinical-natural-language-processing-systems-to-multiple-diverse-health-care-settings
#11
David S Carrell, Robert E Schoen, Daniel A Leffler, Michele Morris, Sherri Rose, Andrew Baer, Seth D Crockett, Rebecca A Gourevitch, Katie M Dean, Ateev Mehrotra
Objective: Widespread application of clinical natural language processing (NLP) systems requires taking existing NLP systems and adapting them to diverse and heterogeneous settings. We describe the challenges faced and lessons learned in adapting an existing NLP system for measuring colonoscopy quality. Materials and Methods: Colonoscopy and pathology reports from 4 settings during 2013-2015, varying by geographic location, practice type, compensation structure, and electronic health record...
April 17, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28412959/opportunities-for-developing-therapies-for-rare-genetic-diseases-focus-on-gain-of-function-and-allostery
#12
Binbin Chen, Russ B Altman
BACKGROUND: Advances in next generation sequencing technologies have revolutionized our ability to discover the causes of rare genetic diseases. However, developing treatments for these diseases remains challenging. In fact, when we systematically analyze the US FDA orphan drug list, we find that only 8% of rare diseases have an FDA-designated drug. Our approach leverages three primary insights: first, diseases with gain-of-function mutations and late onset are more likely to have drug options; second, drugs are more often inhibitors than activators; and third, some disease-causing proteins can be rescued by allosteric activators in diseases due to loss-of-function mutations...
April 17, 2017: Orphanet Journal of Rare Diseases
https://www.readbyqxmd.com/read/28411058/brain-signatures-of-early-lexical-and-morphological-learning-of-a-new-language
#13
Viktória Havas, Matti Laine, Antoni Rodríguez Fornells
Morphology is an important part of language processing but little is known about how adult second language learners acquire morphological rules. Using a word-picture associative learning task, we have previously shown that a brief exposure to novel words with embedded morphological structure (suffix for natural gender) is enough for language learners to acquire the hidden morphological rule. Here we used this paradigm to study the brain signatures of early morphological learning in a novel language in adults...
April 11, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28411030/a-critical-and-interpretive-literature-review-of-birthing-women-s-non-elicited-pain-language
#14
Stephanie Power, Fiona E Bogossian, Roland Sussex, Jenny Strong
BACKGROUND: Standardised pain assessment i.e. the McGill Pain Questionnaire provide an elicited pain language. Midwives observe spontaneous non-elicited pain language to guide their assessment of how a woman is coping with labour. This paper examined the labour pain experience using the questions: What type of pain language do women use? Do any of the words match the descriptors of standardised pain assessments? What type of information doverbal and non-verbal cues provide to the midwife? METHODS: A literature search was conducted in 2013...
April 12, 2017: Women and Birth: Journal of the Australian College of Midwives
https://www.readbyqxmd.com/read/28410513/representation-learning-via-dual-autoencoder-for-recommendation
#15
Fuzhen Zhuang, Zhiqiang Zhang, Mingda Qian, Chuan Shi, Xing Xie, Qing He
Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e.g., social relationships of users and items' attributions, to improve the recommendation performance under the matrix factorization framework. However, matrix factorization methods may not make full use of the limited information from rating or check-in matrices, and achieve unsatisfying results...
March 27, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28410343/patient-understanding-of-the-risks-and-benefits-of-biologic-therapies-in-inflammatory-bowel-disease-insights-from-a-large-scale-analysis-of-social-media-platforms
#16
Bibiana Martinez, Francis Dailey, Christopher V Almario, Michelle S Keller, Mansee Desai, Taylor Dupuy, Sasan Mosadeghi, Cynthia Whitman, Karen Lasch, Lyann Ursos, Brennan M R Spiegel
BACKGROUND: Few studies have examined inflammatory bowel disease (IBD) patients' knowledge and understanding of biologic therapies outside traditional surveys. Here, we used social media data to examine IBD patients' understanding of the risks and benefits associated with biologic therapies and how this affects decision-making. METHODS: We collected posts from Twitter and e-forum discussions from >3000 social media sites posted between June 27, 2012 and June 27, 2015...
April 13, 2017: Inflammatory Bowel Diseases
https://www.readbyqxmd.com/read/28410049/a-customized-attention-based-long-short-term-memory-network-for-distant-supervised-relation-extraction
#17
Dengchao He, Hongjun Zhang, Wenning Hao, Rui Zhang, Kai Cheng
Distant supervision, a widely applied approach in the field of relation extraction can automatically generate large amounts of labeled training corpus with minimal manual effort. However, the labeled training corpus may have many false-positive data, which would hurt the performance of relation extraction. Moreover, in traditional feature-based distant supervised approaches, extraction models adopt human design features with natural language processing. It may also cause poor performance. To address these two shortcomings, we propose a customized attention-based long short-term memory network...
April 14, 2017: Neural Computation
https://www.readbyqxmd.com/read/28408872/social-interaction-affects-neural-outcomes-of-sign-language-learning-as-a-foreign-language-in-adults
#18
Noriaki Yusa, Jungho Kim, Masatoshi Koizumi, Motoaki Sugiura, Ryuta Kawashima
Children naturally acquire a language in social contexts where they interact with their caregivers. Indeed, research shows that social interaction facilitates lexical and phonological development at the early stages of child language acquisition. It is not clear, however, whether the relationship between social interaction and learning applies to adult second language acquisition of syntactic rules. Does learning second language syntactic rules through social interactions with a native speaker or without such interactions impact behavior and the brain? The current study aims to answer this question...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28404537/building-a-comprehensive-syntactic-and-semantic-corpus-of-chinese-clinical-texts
#19
Bin He, Bin Dong, Yi Guan, Jinfeng Yang, Zhipeng Jiang, Qiubin Yu, Jianyi Cheng, Chunyan Qu
OBJECTIVE: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain. MATERIALS AND METHODS: An iterative annotation method was proposed to train annotators and to develop annotation guidelines. Then, by using annotation quality assurance measures, a comprehensive corpus was built, containing annotations of part-of-speech (POS) tags, syntactic tags, entities, assertions, and relations...
April 9, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28403158/what-can-we-learn-from-corporate-sustainability-reporting-deriving-propositions-for-research-and-practice-from-over-9-500-corporate-sustainability-reports-published-between-1999-and-2015-using-topic-modelling-technique
#20
Nadine Székely, Jan Vom Brocke
Organizations are increasingly using sustainability reports to inform their stakeholders and the public about their sustainability practices. We apply topic modelling to 9,514 sustainability reports published between 1999 and 2015 in order to identify common topics and, thus, the most common practices described in these reports. In particular, we identify forty-two topics that reflect sustainability and focus on the coverage and trends of economic, environmental, and social sustainability topics. Among the first to analyse such a large amount of data on organizations' sustainability reporting, the paper serves as an example of how to apply natural language processing as a strategy of inquiry in sustainability research...
2017: PloS One
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