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https://www.readbyqxmd.com/read/28508772/concept-based-retrieval-from-critical-incident-reports
#1
Kerstin Denecke
BACKGROUND: Critical incident reporting systems (CIRS) are used as a means to collect anonymously entered information of incidents that occurred for example in a hospital. Analyzing this information helps to identify among others problems in the workflow, in the infrastructure or in processes. OBJECTIVES: The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval of relevant reports and their analysis is difficult and time-consuming, and the reporting systems often do not provide support for these tasks...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28506958/enhancing-comparative-effectiveness-research-with-automated-pediatric-pneumonia-detection-in-a-multi-institutional-clinical-repository-a-phis-pilot-study
#2
Stephane Meystre, Ramkiran Gouripeddi, Joel Tieder, Jeffrey Simmons, Rajendu Srivastava, Samir Shah
BACKGROUND: Community-acquired pneumonia is a leading cause of pediatric morbidity. Administrative data are often used to conduct comparative effectiveness research (CER) with sufficient sample sizes to enhance detection of important outcomes. However, such studies are prone to misclassification errors because of the variable accuracy of discharge diagnosis codes. OBJECTIVE: The aim of this study was to develop an automated, scalable, and accurate method to determine the presence or absence of pneumonia in children using chest imaging reports...
May 15, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28506904/ordinal-convolutional-neural-networks-for-predicting-rdoc-positive-valence-psychiatric-symptom-severity-scores
#3
Anthony Rios, Ramakanth Kavuluru
BACKGROUND: The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task. OBJECTIVE: Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification...
May 12, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28502651/rack-1-a-multifaceted-regulator-is-required-for-c-%C3%A2-elegans-innate-immunity-against-s-%C3%A2-flexneri-m9ot-infection
#4
Shanmugam Marudhupandiyan, Udayakumar Prithika, Boopathi Balasubramaniam, Krishnaswamy Balamurugan
The nematode C. elegans has the ability to clear off bacterial colonization in the intestine using pathogen specific innate immune response. Here, we show that C. elegans RACK-1 has been vital in determining the survival of worms under specific pathogenic infection. Among various pathogens tested, S. flexneri M9OT (SF) exhibited highest pathogenicity by killing rack-1 mutant worm-VC3013 earlier when compared to WT. The expression level of rack-1 mRNA was found to be decreased and it further indicated that the host translational event appeared to be affected during SF infection...
May 11, 2017: Developmental and Comparative Immunology
https://www.readbyqxmd.com/read/28499156/treatment-of-chemical-cleaning-wastewater-and-cost-optimization-by-response-surface-methodology-coupled-nonlinear-programming
#5
Yang Yang, Zhen Zhou, Chenjie Lu, Yunke Chen, Honghua Ge, Libing Wang, Cheng Cheng
The real alkaline cleaning wastewater (ACW) was treated by a process consisting of neutralization, NaClO oxidation and aluminum sulfate (AS) coagulation, and a novel response surface methodology coupled nonlinear programming (RSM-NLP) approach was developed and used to optimize the oxidation-coagulation process under constraints of relevant discharge standards. Sulfuric acid neutralization effectively removed chemical oxygen demand (COD), surfactant alkylphenol ethoxylates (OP-10) and silicate at the optimum pH of 7...
May 9, 2017: Journal of Environmental Management
https://www.readbyqxmd.com/read/28489820/discovery-of-nitrate-cpk-nlp-signalling-in-central-nutrient-growth-networks
#6
Kun-Hsiang Liu, Yajie Niu, Mineko Konishi, Yue Wu, Hao Du, Hoo Sun Chung, Lei Li, Marie Boudsocq, Matthew McCormack, Shugo Maekawa, Tetsuya Ishida, Chao Zhang, Kevan Shokat, Shuichi Yanagisawa, Jen Sheen
Nutrient signalling integrates and coordinates gene expression, metabolism and growth. However, its primary molecular mechanisms remain incompletely understood in plants and animals. Here we report unique Ca(2+) signalling triggered by nitrate with live imaging of an ultrasensitive biosensor in Arabidopsis leaves and roots. A nitrate-sensitized and targeted functional genomic screen identifies subgroup III Ca(2+)-sensor protein kinases (CPKs) as master regulators that orchestrate primary nitrate responses. A chemical switch with the engineered mutant CPK10(M141G) circumvents embryo lethality and enables conditional analyses of cpk10 cpk30 cpk32 triple mutants to define comprehensive nitrate-associated regulatory and developmental programs...
May 10, 2017: Nature
https://www.readbyqxmd.com/read/28480087/rhodotorula-endogenous-endophthalmitis-a-novel-harbinger-of-the-injection-drug-epidemic-in-the-united-states
#7
Preston M Luong, Basilio Kalpakian, Lawrence J Jaeger, Timothy Lahey, Christopher B Chapman, Michael E Zegans
Endogenous endophthalmitis is a rare but feared infectious ocular complication of injection drug use (IDU). The recent opioid epidemic in the United States threatens to increase the incidence of this disease. We report the first case of endogenous endophthalmitis in the United States caused by the emerging fungal pathogen Rhodotorula in an injection drug user which led to no light perception vision (NLP). Worldwide experience with Rhodotorula endogenous endophthalmitis is limited, but existing cases suggest infection by this particular fungal genus has a grim prognosis...
2017: Case Reports in Infectious Diseases
https://www.readbyqxmd.com/read/28477208/bcc-ner-bidirectional-contextual-clues-named-entity-tagger-for-gene-protein-mention-recognition
#8
Gurusamy Murugesan, Sabenabanu Abdulkadhar, Balu Bhasuran, Jeyakumar Natarajan
Tagging biomedical entities such as gene, protein, cell, and cell-line is the first step and an important pre-requisite in biomedical literature mining. In this paper, we describe our hybrid named entity tagging approach namely BCC-NER (bidirectional, contextual clues named entity tagger for gene/protein mention recognition). BCC-NER is deployed with three modules. The first module is for text processing which includes basic NLP pre-processing, feature extraction, and feature selection. The second module is for training and model building with bidirectional conditional random fields (CRF) to parse the text in both directions (forward and backward) and integrate the backward and forward trained models using margin-infused relaxed algorithm (MIRA)...
December 2017: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/28476375/provider-specific-quality-measurement-for-ercp-using-natural-language-processing
#9
Timothy D Imler, Stuart Sherman, Thomas F Imperiale, Huiping Xu, Fangqian Ouyang, Christopher Beesley, Charity Hilton, Gregory A Coté
BACKGROUND: Natural language processing (NLP) is an information retrieval technique that has been shown to accurately identify quality measures for colonoscopy. There are no systematic methods by which to track adherence to quality measures for ERCP, the highest risk endoscopic procedure widely used in practice. AIM: Our aim was to demonstrate the feasibility of using NLP to measure adherence to ERCP quality indicators across individual providers. METHODS: ERCPs performed by 6 providers at a single institution from 2006 to 2014 were identified...
May 2, 2017: Gastrointestinal Endoscopy
https://www.readbyqxmd.com/read/28468748/twimed-twitter-and-pubmed-comparable-corpus-of-drugs-diseases-symptoms-and-their-relations
#10
Nestor Alvaro, Yusuke Miyao, Nigel Collier
BACKGROUND: Work on pharmacovigilance systems using texts from PubMed and Twitter typically target at different elements and use different annotation guidelines resulting in a scenario where there is no comparable set of documents from both Twitter and PubMed annotated in the same manner. OBJECTIVE: This study aimed to provide a comparable corpus of texts from PubMed and Twitter that can be used to study drug reports from these two sources of information, allowing researchers in the area of pharmacovigilance using natural language processing (NLP) to perform experiments to better understand the similarities and differences between drug reports in Twitter and PubMed...
May 3, 2017: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/28466087/canary-an-nlp-platform-for-clinicians-and-researchers
#11
Shervin Malmasi, Nicolae L Sandor, Naoshi Hosomura, Matt Goldberg, Stephen Skentzos, Alexander Turchin
Information Extraction methods can help discover critical knowledge buried in the vast repositories of unstructured clinical data. However, these methods are underutilized in clinical research, potentially due to the absence of free software geared towards clinicians with little technical expertise. The skills required for developing/using such software constitute a major barrier for medical researchers wishing to employ these methods. To address this, we have developed Canary, a free and open-source solution designed for users without natural language processing (NLP) or software engineering experience...
May 3, 2017: Applied Clinical Informatics
https://www.readbyqxmd.com/read/28462185/a-survey-of-oral-health-in-institutionalized-population-with-intellectual-disabilities-comparison-with-a-national-oral-health-survey-of-the-normal-population
#12
Hicham A Diab, Ghassan N Hamadeh, Fouad Ayoub
INTRODUCTION: Compared to the general population, the intellectually-disabled (ID) experience poor health and inferior access to high quality health services. AIM: To compare the oral health of institutionalized ID Lebanese individuals to that of the normal Lebanese population (NLP). MATERIALS AND METHODS: Caries and periodontal indices were recorded in 652 ID individuals (aged 6, 12, 15, and 35-44 years) residing in the 5 major Lebanese governorates...
March 2017: Journal of International Society of Preventive & Community Dentistry
https://www.readbyqxmd.com/read/28444127/hla-class-i-binding-prediction-via-convolutional-neural-networks
#13
Yeeleng S Vang, Xiaohui Xie
Motivation: Many biological processes are governed by protein-ligand interactions. One such example is the recognition of self and nonself cells by the immune system. This immune response process is regulated by the major histocompatibility complex (MHC) protein which is encoded by the human leukocyte antigen (HLA) complex. Understanding the binding potential between MHC and peptides can lead to the design of more potent, peptide-based vaccines and immunotherapies for infectious autoimmune diseases...
April 21, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28438706/towards-generalizable-entity-centric-clinical-coreference-resolution
#14
Timothy Miller, Dmitriy Dligach, Steven Bethard, Chen Lin, Guergana Savova
OBJECTIVE: This work investigates the problem of clinical coreference resolution in a model that explicitly tracks entities, and aims to measure the performance of that model in both traditional in-domain train/test splits and cross-domain experiments that measure the generalizability of learned models. METHODS: The two methods we compare are a baseline mention-pair coreference system that operates over pairs of mentions with best-first conflict resolution and a mention-synchronous system that incrementally builds coreference chains...
April 21, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28428140/automated-annotation-and-classification-of-bi-rads-assessment-from-radiology-reports
#15
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...
May 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28425575/high-dose-supplementation-of-vitamin-d-affects-measures-of-systemic-inflammation-reductions-in-high-sensitivity-c-reactive-protein-level-and-neutrophil-to-lymphocyte-ratio-nlr-distribution
#16
Seyed-Amir Tabatabaeizadeh, Amir Avan, Afsane Bahrami, Ezzat Khodashenas, Habibollah Esmaeili, Gordon A Ferns, Mojtaba Fattahi Abdizadeh, Majid Ghayour-Mobarhan
BACKGROUND: The prevalence of Vitamin D deficiency is increasing worldwide, which has be shown to be associated with increased risk of cardiovascular disease (CVD), autoimmune disease and metabolic syndrome. These conditions are also associated with a heightened state of inflammation. The aim of the current study was to evaluate the effect of vitamin D supplementation on serum C - reactive protein (CRP) level and Neutrophil-to-lymphocyte ratio (NLR) distribution in a large cohort of adolescent girls...
April 20, 2017: Journal of Cellular Biochemistry
https://www.readbyqxmd.com/read/28423797/htp-nlp-a-new-nlp-system-for-high-throughput-phenotyping
#17
Daniel R Schlegel, Chris Crowner, Frank Lehoullier, Peter L Elkin
Secondary use of clinical data for research requires a method to quickly process the data so that researchers can quickly extract cohorts. We present two advances in the High Throughput Phenotyping NLP system which support the aim of truly high throughput processing of clinical data, inspired by a characterization of the linguistic properties of such data. Semantic indexing to store and generalize partially-processed results and the use of compositional expressions for ungrammatical text are discussed, along with a set of initial timing results for the system...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28423792/acronym-disambiguation-in-spanish-electronic-health-narratives-using-machine-learning-techniques
#18
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/28419261/challenges-in-adapting-existing-clinical-natural-language-processing-systems-to-multiple-diverse-health-care-settings
#19
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/28404537/building-a-comprehensive-syntactic-and-semantic-corpus-of-chinese-clinical-texts
#20
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
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