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https://www.readbyqxmd.com/read/28743623/novel-mannose-binding-natterin-like-protein-in-the-skin-mucus-of-atlantic-cod-gadus-morhua
#1
Binoy Rajan, Deepti M Patel, Yoichiro Kitani, Kiron Viswanath, Monica F Brinchmann
This study presents the first report of purification of natterin-like protein (Nlp) in a non-venomous fish. The peptide identities of purified cod Nlp were confirmed through LC-MSMS and matched to a cod expressed sequence tag (EST). A partial cod nlp nucleotide sequence was amplified and sequenced based on this EST. Multiple sequence alignment of cod Nlp showed considerable homology with other teleost Nlps and the presence of an N-terminal jacalin-like lectin domain coupled with a C-terminal toxin domain. nlp expression was higher in skin, head kidney, liver and spleen than in other tissues studied...
July 22, 2017: Fish & Shellfish Immunology
https://www.readbyqxmd.com/read/28729030/natural-language-processing-systems-for-capturing-and-standardizing-unstructured-clinical-information-a-systematic-review
#2
REVIEW
Kory Kreimeyer, Matthew Foster, Abhishek Pandey, Nina Arya, Gwendolyn Halford, Sandra F Jones, Richard Forshee, Mark Walderhaug, Taxiarchis Botsis
We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers...
July 17, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28716789/identification-of-the-delivery-of-cognitive-behavioural-therapy-for-psychosis-cbtp-using-a-cross-sectional-sample-from-electronic-health-records-and-open-text-information-in-a-large-uk-based-mental-health-case-register
#3
Craig Colling, Lauren Evans, Matthew Broadbent, David Chandran, Thomas J Craig, Anna Kolliakou, Robert Stewart, Philippa A Garety
OBJECTIVE: Our primary objective was to identify cognitive behavioural therapy (CBT) delivery for people with psychosis (CBTp) using an automated method in a large electronic health record database. We also examined what proportion of service users with a diagnosis of psychosis were recorded as having received CBTp within their episode of care during defined time periods provided by early intervention or promoting recovery community services for people with psychosis, compared with published audits and whether demographic characteristics differentially predicted the receipt of CBTp...
July 17, 2017: BMJ Open
https://www.readbyqxmd.com/read/28705240/a-rule-based-electronic-phenotyping-algorithm-for-detecting-clinically-relevant-cardiovascular-disease-cases
#4
Santiago Esteban, Manuel Rodríguez Tablado, Ricardo Ignacio Ricci, Sergio Terrasa, Karin Kopitowski
BACKGROUND: The implementation of electronic medical records (EMR) is becoming increasingly common. Error and data loss reduction, patient-care efficiency increase, decision-making assistance and facilitation of event surveillance, are some of the many processes that EMRs help improve. In addition, they show a lot of promise in terms of data collection to facilitate observational epidemiological studies and their use for this purpose has increased significantly over the recent years...
July 14, 2017: BMC Research Notes
https://www.readbyqxmd.com/read/28699566/entity-recognition-from-clinical-texts-via-recurrent-neural-network
#5
Zengjian Liu, Ming Yang, Xiaolong Wang, Qingcai Chen, Buzhou Tang, Zhe Wang, Hua Xu
BACKGROUND: Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health information (PHI), widely exist in clinical texts. Recognizing these entities has become a hot topic in clinical natural language processing (NLP), and a large number of traditional machine learning methods, such as support vector machine and conditional random field, have been deployed to recognize entities from clinical texts in the past few years...
July 5, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28699546/an-active-learning-enabled-annotation-system-for-clinical-named-entity-recognition
#6
Yukun Chen, Thomas A Lask, Qiaozhu Mei, Qingxia Chen, Sungrim Moon, Jingqi Wang, Ky Nguyen, Tolulola Dawodu, Trevor Cohen, Joshua C Denny, Hua Xu
BACKGROUND: Active learning (AL) has shown the promising potential to minimize the annotation cost while maximizing the performance in building statistical natural language processing (NLP) models. However, very few studies have investigated AL in a real-life setting in medical domain. METHODS: In this study, we developed the first AL-enabled annotation system for clinical named entity recognition (NER) with a novel AL algorithm. Besides the simulation study to evaluate the novel AL algorithm, we further conducted user studies with two nurses using this system to assess the performance of AL in real world annotation processes for building clinical NER models...
July 5, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28682246/breakingnews-article-annotation-by-image-and-text-processing
#7
Arnau Ramisa, Fei Yan, Francesc Moreno-Noguer, Krystian Mikolajczyk
Current approaches lying in the intersection of computer vision and NLP have achieved unprecedented breakthroughs in tasks like automatic captioning or image retrieval. Most of these methods, though, rely on training sets of images associated with annotations that specifically describe the visual content. This paper proposes going a step further and explores more complex cases where textual descriptions are loosely related to images. We focus on the particular domain of News. We introduce new deep learning methods that address source and popularity prediction, article illustration, and article geolocation...
June 30, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28679904/using-structured-and-unstructured-data-to-refine-estimates-of-military-sexual-trauma-status-among-us-military-veterans
#8
Adi V Gundlapalli, Emily Brignone, Guy Divita, Audrey L Jones, Andrew Redd, Ying Suo, Warren B P Pettey, April Mohanty, Lori Gawron, Rebecca Blais, Matthew H Samore, Jamison D Fargo
Sexual trauma survivors are reluctant to disclose such a history due to stigma. This is likely the case when estimating the prevalence of sexual trauma experienced in the military. The Veterans Health Administration has a program by which all former US military service members (Veterans) are screened for military sexual trauma (MST) using a questionnaire. Administrative data on MST screens and a change of status from an initial negative answer to positive and natural language processing (NLP) on electronic medical notes to extract concepts related to MST were used to refine initial estimates of MST among a random sample of 20,000 Veterans...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28664200/an-ontology-enabled-natural-language-processing-pipeline-for-provenance-metadata-extraction-from-biomedical-text-short-paper
#9
Joshua Valdez, Michael Rueschman, Matthew Kim, Susan Redline, Satya S Sahoo
Extraction of structured information from biomedical literature is a complex and challenging problem due to the complexity of biomedical domain and lack of appropriate natural language processing (NLP) techniques. High quality domain ontologies model both data and metadata information at a fine level of granularity, which can be effectively used to accurately extract structured information from biomedical text. Extraction of provenance metadata, which describes the history or source of information, from published articles is an important task to support scientific reproducibility...
October 2016: On Move Meaningful Internet Syst
https://www.readbyqxmd.com/read/28662941/no-light-perception-outcomes-following-boston-keratoprosthesis-type-1-surgery
#10
Adam K Muzychuk, Georges M Durr, Julien J Shine, Marie-Claude Robert, Mona Harissi-Dagher
PURPOSE: To determine the incidence rate, principal causes, and clinical course of eyes developing no light perception (NLP) visual acuity (VA) following Boston Keratoprosthesis (B-KPro) type 1 surgery. Secondary objectives include determining the incidence rate, relative risk (RR), and survival probability with respect to NLP acuity among eyes with congenital aniridia. DESIGN: Retrospective, interventional case series. SUBJECTS: All patients undergoing B-KPro type 1 surgery between Oct...
June 26, 2017: American Journal of Ophthalmology
https://www.readbyqxmd.com/read/28655614/rnai-mediated-disruption-of-neuropeptide-genes-nlp-3-and-nlp-12-cause-multiple-behavioral-defects-in-meloidogyne-incognita
#11
Manoranjan Dash, Tushar K Dutta, Victor Phani, Pradeep K Papolu, Tagginahalli N Shivakumara, Uma Rao
Owing to the current deficiencies in chemical control options and unavailability of novel management strategies, root-knot nematode (M. incognita) infections remain widespread with significant socio-economic impacts. Helminth nervous systems are peptide-rich and appear to be putative drug targets that could be exploited by antihelmintic chemotherapy. Herein, to characterize the novel peptidergic neurotransmitters, in silico mining of M. incognita genomic and transciptomic datasets revealed the presence of 16 neuropeptide-like protein (nlp) genes with structural hallmarks of neuropeptide preproproteins; among which 13 nlps were PCR-amplified and sequenced...
June 24, 2017: Biochemical and Biophysical Research Communications
https://www.readbyqxmd.com/read/28648889/mapping-between-fmri-responses-to-movies-and-their-natural-language-annotations
#12
REVIEW
Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Christopher Baldassano, Janice Chen, Esther Yong, Christopher Honey, Uri Hasson, Peter Ramadge, Kenneth A Norman, Sanjeev Arora
Several research groups have shown how to map fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language annotation is available as the description of the stimulus. We study fMRI data gathered from subjects watching an episode of BBCs Sherlock (Chen et al., 2017), and learn bidirectional mappings between fMRI responses and natural language representations. By leveraging data from multiple subjects watching the same movie, we were able to perform scene classification with 72% accuracy (random guessing would give 4%) and scene ranking with average rank in the top 4% (random guessing would give 50%)...
June 22, 2017: NeuroImage
https://www.readbyqxmd.com/read/28643174/natural-language-processing-for-ehr-based-pharmacovigilance-a-structured-review
#13
REVIEW
Yuan Luo, William K Thompson, Timothy M Herr, Zexian Zeng, Mark A Berendsen, Siddhartha R Jonnalagadda, Matthew B Carson, Justin Starren
The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug events (ADEs) with pharmaceutical products. This article is a comprehensive structured review of recent advances in applying natural language processing (NLP) to electronic health record (EHR) narratives for pharmacovigilance. We review methods of varying complexity and problem focus, summarize the current state-of-the-art in methodology advancement, discuss limitations and point out several promising future directions...
June 22, 2017: Drug Safety: An International Journal of Medical Toxicology and Drug Experience
https://www.readbyqxmd.com/read/28634427/leveraging-food-and-drug-administration-adverse-event-reports-for-the-automated-monitoring-of-electronic-health-records-in-a-pediatric-hospital
#14
Huaxiu Tang, Imre Solti, Eric Kirkendall, Haijun Zhai, Todd Lingren, Jaroslaw Meller, Yizhao Ni
The objective of this study was to determine whether the Food and Drug Administration's Adverse Event Reporting System (FAERS) data set could serve as the basis of automated electronic health record (EHR) monitoring for the adverse drug reaction (ADR) subset of adverse drug events. We retrospectively collected EHR entries for 71 909 pediatric inpatient visits at Cincinnati Children's Hospital Medical Center. Natural language processing (NLP) techniques were used to identify positive diseases/disorders and signs/symptoms (DDSSs) from the patients' clinical narratives...
2017: Biomedical Informatics Insights
https://www.readbyqxmd.com/read/28634104/natural-language-processing-for-asthma-ascertainment-in-different-practice-settings
#15
Chung-Il Wi, Sunghwan Sohn, Mir Ali, Elizabeth Krusemark, Euijung Ryu, Hongfang Liu, Young J Juhn
BACKGROUND: We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic. OBJECTIVE: To adapt NLP-PAC in a different health care setting, Sanford Children Hospital, by assessing its external validity. METHODS: The study was designed as a retrospective cohort study that used a random sample of 2011-2012 Sanford Birth cohort (n = 595)...
June 17, 2017: Journal of Allergy and Clinical Immunology in Practice
https://www.readbyqxmd.com/read/28616910/-effects-of-limb-ischemic-postconditioning-on-behavioral-improvement-and-proliferation-of-neural-cells-in-rats-with-transient-cerebral-ischemia
#16
Dan Huang, Hong-Hong Liu, Zhen Yang, Yun Qu
OBJECTIVES: To determine the effects of non-invasive limb ischemic postconditioning (NLIP) on the behavioral performance and the expression and distribution of neural cells in rats with ischemic cortex. METHODS: Rats were randomly divided into 3 groups: sham group (n=10), ischemia/reperfusion (I/R) group (n=50), and NLIP group (n=50). Focal cerebral ischemia was induced by intraluminal MCAO in the rats in the I/R and NLIP groups, while no suture was inserted in the sham-operated rats...
May 2017: Sichuan da Xue Xue Bao. Yi Xue Ban, Journal of Sichuan University. Medical Science Edition
https://www.readbyqxmd.com/read/28614702/de-identification-of-psychiatric-intake-records-overview-of-2016-cegs-n-grid-shared-tasks-track-1
#17
Amber Stubbs, Michele Filannino, Özlem Uzuner
The 2016 CEGS N-GRID shared tasks for clinical records contained three tracks. Track 1 focused on de-identification of a new corpus of 1000 psychiatric intake records. This track tackled de-identification in two sub-tracks: Track 1.A was a "sight unseen" task, where nine teams ran existing de-identification systems, without any modifications or training, on 600 new records in order to gauge how well systems generalize to new data. The best-performing system for this track scored an F1 of 0.799. Track 1.B was a traditional Natural Language Processing (NLP) shared task on de-identification, where 15 teams had two months to train their systems on the new data, then test it on an unannotated test set...
June 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28613206/-evolution-from-percutaneous-nephrolithotomy-to-mini-pcnl-in-supine-position-on-the-treatment-of-complex-renal-calculi-feasibility-study
#18
Fernando Ramón de Fata-Chillón, Helena Gimbernat-Díaz, Cristina Redondo-Redondo, Elisa Meilán-Hernández, Erika Mateo-Martínez
OBJECTIVES: Mini-PCNL is a potentially less invasive technique than standard percutaneous nephrolithotomy (PCNL). We present our experience and results comparing both approaches in large burden complex renal calculi. METHODS: Prospective non randomized study comparing PCNL (24/26F nephroscope; Group A) and Mini-PCNL (15/18F; Group B) perioperative and postoperative results, in 40 (20 each group) consecutive patients between 2013 and 2014. We analyze demographic data, hemoglobin drop, urine culture, stone characteristics, operative time, puncture, number and size of the tract, disintegration energy sources, nephrostomy placement, hospital stay, stone free rate and Clavien-Dindo complications...
June 2017: Archivos Españoles de Urología
https://www.readbyqxmd.com/read/28606869/predicting-mental-conditions-based-on-history-of-present-illness-in-psychiatric-notes-with-deep-neural-networks
#19
Tung Tran, Ramakanth Kavuluru
BACKGROUND: Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task. OBJECTIVE: We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient's history of present illness typically occurring in the beginning of a psychiatric initial evaluation note...
June 10, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28598934/feasibility-and-utility-of-lexical-analysis-for-occupational-health-text
#20
Philip Harber, Gondy Leroy
OBJECTIVE: Assess feasibility and potential utility of natural language processing (NLP) for storing and analyzing occupational health data. METHODS: Basic NLP lexical analysis methods were applied to 89,000 Mine Safety and Health Administration (MSHA) free text records. Steps included tokenization, term and co-occurrence counts, term annotation, and identifying exposure-health effect relationships. Presence of terms in the Unified Medical Language System (UMLS) was assessed...
June 2017: Journal of Occupational and Environmental Medicine
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