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"Natural Language Processing"

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https://www.readbyqxmd.com/read/27919387/impacts-of-structuring-the-electronic-health-record-results-of-a-systematic-literature-review-from-the-perspective-of-secondary-use-of-patient-data
#1
REVIEW
Riikka Vuokko, Päivi Mäkelä-Bengs, Hannele Hyppönen, Minna Lindqvist, Persephone Doupi
PURPOSE: To explore the impacts that structuring of electronic health records (EHRs) has had from the perspective of secondary use of patient data as reflected in currently published literature. This paper presents the results of a systematic literature review aimed at answering the following questions; (1) what are the common methods of structuring patient data to serve secondary use purposes; (2) what are the common methods of evaluating patient data structuring in the secondary use context, and (3) what impacts or outcomes of EHR structuring have been reported from the secondary use perspective...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27918181/comparing-vector-based-and-bayesian-memory-models-using-large-scale-datasets-user-generated-hashtag-and-tag-prediction-on-twitter-and-stack-overflow
#2
Clayton Stanley, Michael D Byrne
The growth of social media and user-created content on online sites provides unique opportunities to study models of human declarative memory. By framing the task of choosing a hashtag for a tweet and tagging a post on Stack Overflow as a declarative memory retrieval problem, 2 cognitively plausible declarative memory models were applied to millions of posts and tweets and evaluated on how accurately they predict a user's chosen tags. An ACT-R based Bayesian model and a random permutation vector-based model were tested on the large data sets...
December 2016: Psychological Methods
https://www.readbyqxmd.com/read/27903489/finding-important-terms-for-patients-in-their-electronic-health-records-a-learning-to-rank-approach-using-expert-annotations
#3
Jinying Chen, Jiaping Zheng, Hong Yu
BACKGROUND: Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them...
November 30, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27889399/a-natural-language-processing-based-model-to-automate-mri-brain-protocol-selection-and-prioritization
#4
Andrew D Brown, Thomas R Marotta
RATIONALE AND OBJECTIVES: Incorrect imaging protocol selection can contribute to increased healthcare cost and waste. To help healthcare providers improve the quality and safety of medical imaging services, we developed and evaluated three natural language processing (NLP) models to determine whether NLP techniques could be employed to aid in clinical decision support for protocoling and prioritization of magnetic resonance imaging (MRI) brain examinations. MATERIALS AND METHODS: To test the feasibility of using an NLP model to support clinical decision making for MRI brain examinations, we designed three different medical imaging prediction tasks, each with a unique outcome: selecting an examination protocol, evaluating the need for contrast administration, and determining priority...
November 23, 2016: Academic Radiology
https://www.readbyqxmd.com/read/27882837/determining-multiple-sclerosis-phenotype-from-electronic-medical-records
#5
Richard E Nelson, Jorie Butler, Joanne LaFleur, Kristin Knippenberg, Aaron W C Kamauu, Scott L DuVall
BACKGROUND: Multiple sclerosis (MS), a central nervous system disease in which nerve signals are disrupted by scarring and demyelination, is classified into phenotypes depending on the patterns of cognitive or physical impairment progression: relapsing-remitting MS (RRMS), primary-progressive MS (PPMS), secondary-progressive MS (SPMS), or progressive-relapsing MS (PRMS). The phenotype is important in managing the disease and determining appropriate treatment. The ICD-9-CM code 340.0 is uninformative about MS phenotype, which increases the difficulty of studying the effects of phenotype on disease...
December 2016: Journal of Managed Care & Specialty Pharmacy
https://www.readbyqxmd.com/read/27864252/predictors-of-care-home-and-hospital-admissions-and-their-costs-for-older-people-with-alzheimer-s-disease-findings-from-a-large-london-case-register
#6
Martin Knapp, Kia-Chong Chua, Matthew Broadbent, Chin-Kuo Chang, Jose-Luis Fernandez, Dominique Milea, Renee Romeo, Simon Lovestone, Michael Spencer, Gwilym Thompson, Robert Stewart, Richard D Hayes
OBJECTIVES: To examine links between clinical and other characteristics of people with Alzheimer's disease living in the community, likelihood of care home or hospital admission, and associated costs. DESIGN: Observational data extracted from clinical records using natural language processing and Hospital Episode Statistics. Statistical analyses examined effects of cognition, physical health, mental health, sociodemographic factors and living circumstances on risk of admission to care home or hospital over 6 months and associated costs, adjusting for repeated observations...
November 18, 2016: BMJ Open
https://www.readbyqxmd.com/read/27859320/advanced-literature-analysis-in-a-big-data-world
#7
Chris Cheadle, Hongbao Cao, Andrey Kalinin, Jaqui Hodgkinson
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological information from journal articles and abstracts that is then used to create a very large, structured, and constantly expanding literature knowledgebase. Highly sophisticated visualization tools allow the user to interactively explore the vast number of connections created and stored in the Pathway Studio database...
November 10, 2016: Annals of the New York Academy of Sciences
https://www.readbyqxmd.com/read/27845806/hospitalized-older-adults-with-established-delirium-recognition-documentation-and-reporting
#8
Margarete L Zalon, Sonia Sandhaus, Mary Kovaleski, Paula Roe-Prior
Delirium, a life-threatening complication for hospitalized older adults associated with adverse outcomes, is often underrecognized and underreported. The purpose of the current study was to analyze delirium documentation for hospitalized older adults. Charts of 34 patients, aged 71 and older with documented delirium and referral to a Hospital Elder Life Program, were reviewed. With the exception of International Classification of Diseases-9 coding, delirium was only mentioned in 12 (35.3%) charts, although descriptors potentially indicative of delirium were usually recorded...
November 15, 2016: Journal of Gerontological Nursing
https://www.readbyqxmd.com/read/27836816/web-based-real-time-case-finding-for-the-population-health-management-of-patients-with-diabetes-mellitus-a-prospective-validation-of-the-natural-language-processing-based-algorithm-with-statewide-electronic-medical-records
#9
Le Zheng, Yue Wang, Shiying Hao, Andrew Y Shin, Bo Jin, Anh D Ngo, Medina S Jackson-Browne, Daniel J Feller, Tianyun Fu, Karena Zhang, Xin Zhou, Chunqing Zhu, Dorothy Dai, Yunxian Yu, Gang Zheng, Yu-Ming Li, Doff B McElhinney, Devore S Culver, Shaun T Alfreds, Frank Stearns, Karl G Sylvester, Eric Widen, Xuefeng Bruce Ling
BACKGROUND: Diabetes case finding based on structured medical records does not fully identify diabetic patients whose medical histories related to diabetes are available in the form of free text. Manual chart reviews have been used but involve high labor costs and long latency. OBJECTIVE: This study developed and tested a Web-based diabetes case finding algorithm using both structured and unstructured electronic medical records (EMRs). METHODS: This study was based on the health information exchange (HIE) EMR database that covers almost all health facilities in the state of Maine, United States...
November 11, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27830256/clinical-natural-language-processing-in-2015-leveraging-the-variety-of-texts-of-clinical-interest
#10
A Névéol, P Zweigenbaum
OBJECTIVE: To summarize recent research and present a selection of the best papers published in 2015 in the field of clinical Natural Language Processing (NLP). METHOD: A systematic review of the literature was performed by the two section editors of the IMIA Yearbook NLP section by searching bibliographic databases with a focus on NLP efforts applied to clinical texts or aimed at a clinical outcome. Section editors first selected a shortlist of candidate best papers that were then peer-reviewed by independent external reviewers...
November 10, 2016: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/27830255/aspiring-to-unintended-consequences-of-natural-language-processing-a-review-of-recent-developments-in-clinical-and-consumer-generated-text-processing
#11
D Demner-Fushman, N Elhadad
OBJECTIVES: This paper reviews work over the past two years in Natural Language Processing (NLP) applied to clinical and consumer-generated texts. METHODS: We included any application or methodological publication that leverages text to facilitate healthcare and address the health-related needs of consumers and populations. RESULTS: Many important developments in clinical text processing, both foundational and task-oriented, were addressed in community- wide evaluations and discussed in corresponding special issues that are referenced in this review...
November 10, 2016: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/27826610/identification-of-long-bone-fractures-in-radiology-reports-using-natural-language-processing-to-support-healthcare-quality-improvement
#12
Robert W Grundmeier, Aaron J Masino, T Charles Casper, Jonathan M Dean, Jamie Bell, Rene Enriquez, Sara Deakyne, James M Chamberlain, Elizabeth R Alpern
BACKGROUND: Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely been applied outside the research laboratories where they were developed. OBJECTIVE: To implement and validate NLP tools to identify long bone fractures for pediatric emergency medicine quality improvement. METHODS: Using freely available statistical software packages, we implemented NLP methods to identify long bone fractures from radiology reports...
November 9, 2016: Applied Clinical Informatics
https://www.readbyqxmd.com/read/27825333/data-extraction-from-electronic-health-records-ehrs-for-quality-measurement-of-the-physical-therapy-process-comparison-between-ehr-data-and-survey-data
#13
Marijn Scholte, Simone A van Dulmen, Catherina W M Neeleman-Van der Steen, Philip J van der Wees, Maria W G Nijhuis-van der Sanden, Jozé Braspenning
BACKGROUND: With the emergence of the electronic health records (EHRs) as a pervasive healthcare information technology, new opportunities and challenges for use of clinical data for quality measurements arise with respect to data quality, data availability and comparability. The objective of this study is to test whether data extracted from electronic health records (EHRs) was of comparable quality as survey data for the calculation of quality indicators. METHODS: Data from surveys describing patient cases and filled out by physiotherapists in 2009-2010 were used to calculate scores on eight quality indicators (QIs) to measure the quality of physiotherapy care...
November 8, 2016: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/27815227/can-multilinguality-improve-biomedical-word-sense-disambiguation
#14
Andres Duque, Juan Martinez-Romo, Lourdes Araujo
Ambiguity in the biomedical domain represents a major issue when performing Natural Language Processing tasks over the huge amount of available information in the field. For this reason, Word Sense Disambiguation is critical for achieving accurate systems able to tackle complex tasks such as information extraction, summarization or document classification. In this work we explore whether multilinguality can help to solve the problem of ambiguity, and the conditions required for a system to improve the results obtained by monolingual approaches...
December 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/27813310/identifying-axial-spondyloarthritis-in-electronic-medical-records-of-united-states-veterans
#15
Jessica A Walsh, Yijun Shao, Jianwei Leng, Tao He, Chia-Chen Teng, Doug Redd, Qing Treitler Zeng, Zachary Burningham, Daniel O Clegg, Brian C Sauer
OBJECTIVE: Large database research in axial spondyloarthritis (AxSpA) is limited by a lack of methods for identifying most types of AxSpA. Our objective was to develop methods for identifying AxSpA concepts in the free text of documents from electronic medical records. METHODS: Veterans with documents in the national Veteran Health Administration Corporate Data Warehouse between January 1, 2005 and June 30, 2015 were included. Methods were developed for exploring, selecting, and extracting meaningful terms that were likely to represent AxSpA concepts...
November 3, 2016: Arthritis Care & Research
https://www.readbyqxmd.com/read/27810481/evaluating-semantic-similarity-between-chinese-biomedical-terms-through-multiple-ontologies-with-score-normalization-an-initial-study
#16
Wenxin Ning, Ming Yu, Dehua Kong
BACKGROUND: Semantic similarity estimation significantly promotes the understanding of natural language resources and supports medical decision making. Previous studies have investigated semantic similarity and relatedness estimation between biomedical terms through resources in English, such as SNOMED-CT or UMLS. However, very limited studies focused on the Chinese language, and technology on natural language processing and text mining of medical documents in China is urgently needed...
December 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/27793791/natural-language-processing-enabled-and-conventional-data-capture-methods-for-input-to-electronic-health-records-a-comparative-usability-study
#17
David R Kaufman, Barbara Sheehan, Peter Stetson, Ashish R Bhatt, Adele I Field, Chirag Patel, James Mark Maisel
BACKGROUND: The process of documentation in electronic health records (EHRs) is known to be time consuming, inefficient, and cumbersome. The use of dictation coupled with manual transcription has become an increasingly common practice. In recent years, natural language processing (NLP)-enabled data capture has become a viable alternative for data entry. It enables the clinician to maintain control of the process and potentially reduce the documentation burden. The question remains how this NLP-enabled workflow will impact EHR usability and whether it can meet the structured data and other EHR requirements while enhancing the user's experience...
October 28, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27779621/a-studyforrest-extension-simultaneous-fmri-and-eye-gaze-recordings-during-prolonged-natural-stimulation
#18
Michael Hanke, Nico Adelhöfer, Daniel Kottke, Vittorio Iacovella, Ayan Sengupta, Falko R Kaule, Roland Nigbur, Alexander Q Waite, Florian Baumgartner, Jörg Stadler
Here we present an update of the studyforrest (http://studyforrest.org) dataset that complements the previously released functional magnetic resonance imaging (fMRI) data for natural language processing with a new two-hour 3 Tesla fMRI acquisition while 15 of the original participants were shown an audio-visual version of the stimulus motion picture. We demonstrate with two validation analyses that these new data support modeling specific properties of the complex natural stimulus, as well as a substantial within-subject BOLD response congruency in brain areas related to the processing of auditory inputs, speech, and narrative when compared to the existing fMRI data for audio-only stimulation...
October 25, 2016: Scientific Data
https://www.readbyqxmd.com/read/27762013/a-novel-approach-to-virtual-patient-simulation-using-natural-language-processing
#19
Amit Persad, Eleni Stroulia, Sarah Forgie
No abstract text is available yet for this article.
November 2016: Medical Education
https://www.readbyqxmd.com/read/27754498/investigating-the-association-between-sociodemographic-factors-and-lung-cancer-risk-using-cyber-informatics
#20
Hong-Jun Yoon, Georgia Tourassi
Openly available online sources can be very valuable for executing in silico case-control epidemiological studies. Adjustment of confounding factors to isolate the association between an observing factor and disease is essential for such studies. However, such information is not always readily available online. This paper suggests natural language processing methods for extracting socio-demographic information from content openly available online. Feasibility of the suggested method is demonstrated by performing a case-control study focusing on the association between age, gender, and income level and lung cancer risk...
February 2016: ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics
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