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"Natural Language Processing"

Benjamin L Cook, Ana M Progovac, Pei Chen, Brian Mullin, Sherry Hou, Enrique Baca-Garcia
Natural language processing (NLP) and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain. Participants responded to structured mental and physical health instruments at multiple follow-up points. Outcome variables of interest were suicidal ideation and psychiatric symptoms (GHQ-12). Predictor variables included structured items (e.g., relating to sleep and well-being) and responses to one unstructured question, "how do you feel today?" We compared NLP-based models using the unstructured question with logistic regression prediction models using structured data...
2016: Computational and Mathematical Methods in Medicine
Anthony P Nunes, Jing Yang, Larry Radican, Samuel S Engel, Karen Kurtyka, Kaan Tunceli, Shengsheng Yu, Kristy Iglay, Michael C Doherty, David D Dore
AIMS: Accurate measures of hypoglycemia within electronic health records (EHR) can facilitate clinical population management and research. We quantify the occurrence of serious and mild-to-moderate hypoglycemia in a large EHR database in the US, comparing estimates based only on structured data to those from structured data and natural language processing (NLP) of clinical notes. METHODS: This cohort study included patients with type 2 diabetes identified from January 2009 through March 2014...
September 21, 2016: Diabetes Research and Clinical Practice
Jey Han Lau, Alexander Clark, Shalom Lappin
The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. These judgements are gradient in nature, and so cannot be directly accommodated in a binary formal grammar. However, it is also not possible to simply reduce acceptability to probability...
October 12, 2016: Cognitive Science
Robert Eugene Hoyt, Dallas Snider, Carla Thompson, Sarita Mantravadi
BACKGROUND: We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS)...
October 11, 2016: JMIR Public Health and Surveillance
Erinç Gökdeniz, Arzucan Özgür, Reşit Canbeyli
Identifying the relations among different regions of the brain is vital for a better understanding of how the brain functions. While a large number of studies have investigated the neuroanatomical and neurochemical connections among brain structures, their specific findings are found in publications scattered over a large number of years and different types of publications. Text mining techniques have provided the means to extract specific types of information from a large number of publications with the aim of presenting a larger, if not necessarily an exhaustive picture...
2016: Frontiers in Neuroinformatics
Kersten Döring, Björn A Grüning, Kiran K Telukunta, Philippe Thomas, Stefan Günther
Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools...
2016: PloS One
Anna Jordanous, Bill Keller
Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept...
2016: PloS One
David Kauchak, Gondy Leroy
Limited health literacy is a barrier to understanding health information. Simplifying text can reduce this barrier and possibly other known disparities in health. Unfortunately, few tools exist to simplify text with demonstrated impact on comprehension. By leveraging modern data sources integrated with natural language processing algorithms, we are developing the first semi-automated text simplification tool. We present two main contributions. First, we introduce our evidence-based development strategy for designing effective text simplification software and summarize initial, promising results...
May 2016: IT Professional
Behrouz Bokharaeian, Alberto Diaz, Hamidreza Chitsaz
MOTIVATION: Supervised biomedical relation extraction plays an important role in biomedical natural language processing, endeavoring to obtain the relations between biomedical entities. Drug-drug interactions, which are investigated in the present paper, are notably among the critical biomedical relations. Thus far many methods have been developed with the aim of extracting DDI relations. However, unfortunately there has been a scarcity of comprehensive studies on the effects of negation, complex sentences, clause dependency, and neutral candidates in the course of DDI extraction from biomedical articles...
2016: PloS One
Christopher Andrew Bail
Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-ranging conversation among social media users, whereas the vast majority of them receive little or no attention. I argue that advocacy organizations are more likely to inspire comments from new social media audiences if they create "cultural bridges," or produce messages that combine conversational themes within an advocacy field that are seldom discussed together...
September 30, 2016: Proceedings of the National Academy of Sciences of the United States of America
Zihao Yan, Ivan K Ip, Ali S Raja, Anurag Gupta, Joshua M Kosowsky, Ramin Khorasani
Purpose To determine the frequency of, and yield after, provider overrides of evidence-based clinical decision support (CDS) for ordering computed tomographic (CT) pulmonary angiography in the emergency department (ED). Materials and Methods This HIPAA-compliant, institutional review board-approved study was performed at a tertiary care, academic medical center ED with approximately 60 000 annual visits and included all patients who were suspected of having pulmonary embolism (PE) and who underwent CT pulmonary angiography between January 1, 2011, and August 31, 2013...
September 30, 2016: Radiology
Erin Holve, Samantha Weiss
In September 2015 the EDM Forum hosted AcademyHealth's newest national conference, Concordium. The 11 papers featured in the eGEMs "Concordium 2015" special issue successfully reflect the major themes and issues discussed at the meeting. Many of the papers address informatics or methodological approaches to natural language processing (NLP) or text analysis, which is indicative of the importance of analyzing text data to gain insights into care coordination and patient-centered outcomes. Perspectives on the tools and infrastructure requirements that are needed to build learning health systems were also recurrent themes...
2016: EGEMS
Guy Divita, Marjorie E Carter, Le-Thuy Tran, Doug Redd, Qing T Zeng, Scott Duvall, Matthew H Samore, Adi V Gundlapalli
INTRODUCTION: Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of "best-of-breed" functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support. BACKGROUND: MetaMap, cTAKES and similar well-known natural language processing (NLP) tools do not have sufficient scalability out of the box...
2016: EGEMS
Donald A Szlosek, Jonathan Ferrett
INTRODUCTION: As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation...
2016: EGEMS
Maya S Safarova, Hongfang Liu, Iftikhar J Kullo
BACKGROUND: Little is known about prevalence, awareness, and control of familial hypercholesterolemia (FH) in the United States. OBJECTIVE: To address these knowledge gaps, we developed an ePhenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and deployed it in the Screening Employees And Residents in the Community for Hypercholesterolemia (SEARCH) study. METHODS: We queried a database of 131,000 individuals seen between 1993 and 2014 in primary care practice to identify 5992 (mean age 52 ± 13 years, 42% men) patients with low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, triglycerides <400 mg/dL and without secondary causes of hyperlipidemia...
September 2016: Journal of Clinical Lipidology
Matthew C Swain, Jacqueline M Cole
The emergence of "big data" initiatives has led to the need for tools that can automatically extract valuable chemical information from large volumes of unstructured data, such as the scientific literature. Since chemical information can be present in figures, tables, and textual paragraphs, successful information extraction often depends on the ability to interpret all of these domains simultaneously. We present a complete toolkit for the automated extraction of chemical entities and their associated properties, measurements, and relationships from scientific documents that can be used to populate structured chemical databases...
October 6, 2016: Journal of Chemical Information and Modeling
Maxim Topaz, Kenneth Lai, Dawn Dowding, Victor J Lei, Anna Zisberg, Kathryn H Bowles, Li Zhou
BACKGROUND: Electronic health records are being increasingly used by nurses with up to 80% of the health data recorded as free text. However, only a few studies have developed nursing-relevant tools that help busy clinicians to identify information they need at the point of care. OBJECTIVE: This study developed and validated one of the first automated natural language processing applications to extract wound information (wound type, pressure ulcer stage, wound size, anatomic location, and wound treatment) from free text clinical notes...
September 19, 2016: International Journal of Nursing Studies
Farhood Farjah, Scott Halgrim, Diana S M Buist, Michael K Gould, Steven B Zeliadt, Elizabeth T Loggers, David S Carrell
INTRODUCTION: The incidence of incidentally detected lung nodules is rapidly rising, but little is known about their management or associated patient outcomes. One barrier to studying lung nodule care is the inability to efficiently and reliably identify the cohort of interest (i.e. cases). Investigators at Kaiser Permanente Southern California (KPSC) recently developed an automated method to identify individuals with an incidentally discovered lung nodule, but the feasibility of implementing this method across other health systems is unknown...
2016: EGEMS
Manana Khachidze, Magda Tsintsadze, Maia Archuadze
According to the Ministry of Labor, Health and Social Affairs of Georgia a new health management system has to be introduced in the nearest future. In this context arises the problem of structuring and classifying documents containing all the history of medical services provided. The present work introduces the instrument for classification of medical records based on the Georgian language. It is the first attempt of such classification of the Georgian language based medical records. On the whole 24.855 examination records have been studied...
2016: BioMed Research International
Ignacio Atal, Jean-David Zeitoun, Aurélie Névéol, Philippe Ravaud, Raphaël Porcher, Ludovic Trinquart
BACKGROUND: Clinical trial registries may allow for producing a global mapping of health research. However, health conditions are not described with standardized taxonomies in registries. Previous work analyzed clinical trial registries to improve the retrieval of relevant clinical trials for patients. However, no previous work has classified clinical trials across diseases using a standardized taxonomy allowing a comparison between global health research and global burden across diseases...
2016: BMC Bioinformatics
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