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Dorin Yael, Jacob J Vecht, Izhar Bar-Gad
Filters are widely used for the modulation, typically attenuation, of amplitudes of different frequencies within neurophysiological signals. Filters, however, also induce changes in the phases of different frequencies whose amplitude is unmodulated. These phase shifts cause time lags in the filtered signals, leading to a disruption of the timing information between different frequencies within the same signal and between different signals. The emerging time lags can be either constant in the case of linear phase (LP) filters or vary as a function of the frequency in the more common case of non-LP (NLP) filters...
March 2018: ENeuro
Gokhan Bakal, Preetham Talari, Elijah V Kakani, Ramakanth Kavuluru
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying different causal relations between biomedical entities is also critical to understand biomedical processes. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach...
May 12, 2018: Journal of Biomedical Informatics
H Y Zhou, J J Ye, Y Y Chen, F T Dong
Objective: To evaluate the efficacy of vitrectomy and etiological diagnosis in the treatment of fungal endophthalmitis. Methods: A retrospective survey was done on the clinical manifestation, etiological diagnosis and treatment efficacy of 15 patients (15 eyes) who had been diagnosed with fungal endophthalmitis at the inpatient department of Peking Union Medical College Hospital during 2002-2015. A total of 15 eyes of 15 patients, 3 male and 12 female patients, were included in this study. The mean age of the patients was (45...
April 11, 2018: [Zhonghua Yan Ke za Zhi] Chinese Journal of Ophthalmology
Andrea C Fernandes, Rina Dutta, Sumithra Velupillai, Jyoti Sanyal, Robert Stewart, David Chandran
Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information extraction from free text notes as well as structured fields concerning suicidality and this allows access to much larger cohorts than previously possible. This paper presents two novel NLP approaches - a rule-based approach to classify the presence of suicide ideation and a hybrid machine learning and rule-based approach to identify suicide attempts in a psychiatric clinical database...
May 9, 2018: Scientific Reports
Lorena Endara, Hong Cui, J Gordon Burleigh
Premise of the Study: Phenotypic data sets are necessary to elucidate the genealogy of life, but assembling phenotypic data for taxa across the tree of life can be technically challenging and prohibitively time consuming. We describe a semi-automated protocol to facilitate and expedite the assembly of phenotypic character matrices of plants from formal taxonomic descriptions. This pipeline uses new natural language processing (NLP) techniques and a glossary of over 9000 botanical terms...
March 2018: Applications in Plant Sciences
Kalpana Raja, Jeyakumar Natarajan
BACKGROUND: Extraction of protein phosphorylation information from biomedical literature has gained much attention because of the importance in numerous biological processes. OBJECTIVE: In this study, we propose a text mining methodology which consists of two phases, NLP parsing and SVM classification to extract phosphorylation information from literature. METHODS: First, using NLP parsing we divide the data into three base-forms depending on the biomedical entities related to phosphorylation and further classify into ten sub-forms based on their distribution with phosphorylation keyword...
July 2018: Computer Methods and Programs in Biomedicine
Matthias Löbe, Sebastian Stäubert, Colleen Goldberg, Ivonne Haffner, Alfred Winter
BACKGROUND: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES: This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals...
2018: Studies in Health Technology and Informatics
Farhang Aliakbari, Hossein Mohammad-Beigi, Nasrollah Rezaei-Ghaleh, Stefan Becker, Faezeh Dehghani Esmatabad, Hadieh Alsadat Eslampanah Seyedi, Hassan Bardania, Amir Tayaranian Marvian, Joanna F Collingwood, Gunna Christiansen, Markus Zweckstetter, Daniel E Otzen, Dina Morshedi
The protein α-synuclein (αSN) aggregates to form fibrils in neuronal cells of Parkinson's patients. Here we report on the effect of neutral (zwitterionic) nanoliposomes (NLPs), supplemented with cholesterol (NLP-Chol) and decorated with PEG (NLP-Chol-PEG), on αSN aggregation and neurotoxicity. Both NLPs retard αSN fibrillization in a concentration-independent fashion. They do so largely by increasing lag time (formation of fibrillization nuclei) rather than elongation (extension of existing nuclei). Interactions between neutral NLPs and αSN may locate to the N-terminus of the protein...
May 4, 2018: Nanoscale
Tobias Clark, Vera Hapiak, Mitchell Oakes, Holly Mills, Richard Komuniecki
Monoamines and neuropeptides often modulate the same behavior, but monoaminergic-peptidergic crosstalk remains poorly understood. In Caenorhabditis elegans, the adrenergic-like ligands, tyramine (TA) and octopamine (OA) require distinct subsets of neuropeptides in the two ASI sensory neurons to inhibit nociception. TA selectively increases the release of ASI neuropeptides encoded by nlp-14 or nlp-18 from either synaptic/perisynaptic regions of ASI axons or the ASI soma, respectively, and OA selectively increases the release of ASI neuropeptides encoded by nlp-9 asymmetrically, from only the synaptic/perisynaptic region of the right ASI axon...
2018: PloS One
I-Li Lai, Han-Tsung Liao
BACKGROUND: The optimal management of indirect traumatic optic neuropathy (TON) is controversial. We aimed to compare the differences in visual improvement by treatment option in patients presenting with TON and no light perception (NLP). We also wanted to identify any patient-related factors that might favor the use of SPT or OND. MATERIAL AND METHODS: We retrospectively identified 46 consecutive patients with indirect TON treated at Chang Gung Memorial Hospital between 2007 and 2015...
April 26, 2018: World Neurosurgery
Andrew E Levy, Nishant R Shah, Michael E Matheny, Ruth M Reeves, Glenn T Gobbel, Steven M Bradley
BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate descriptive data to use NLP. METHODS: Among VA patients who underwent stress MPI and coronary angiography between January 1, 2009 and December 31, 2011, 99 stress test reports were randomly selected for analysis...
April 25, 2018: Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology
Jennifer Nayor, Lawrence F Borges, Sergey Goryachev, Vivian S Gainer, John R Saltzman
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured or free text data. AIMS: (1) To develop and validate an accurate automated process for calculation of adenoma detection rate (ADR) and serrated polyp detection rate (SDR) on data stored in widely used electronic health record systems, specifically Epic electronic health record system, Provation® endoscopy reporting system, and Sunquest PowerPath pathology reporting system...
April 26, 2018: Digestive Diseases and Sciences
Zhongliang Yang, Yongfeng Huang, Yiran Jiang, Yuxi Sun, Yu-Jin Zhang, Pengcheng Luo
Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases...
April 20, 2018: Scientific Reports
F M Sánchez-Martín, E Emiliani, E Pueyo-Morer, O Angerri-Feu, F Sanguedolce, F Millán, H Villavicencio
INTRODUCTION: There are currently 3holmium laser, YAG (Ho:YAG) endolithotripsy procedures that are considered basic (fragmentation, pulverisation, "pop-corn" technique). We present the technique of fragmentation targeted at preferred discontinuities (FTPD), a new concept of endolithotripsy by Ho:YAG laser. MATERIAL AND METHODS: The FTPD technique is based on the selective application of energy (targeting a specific preselected point) to an area that is visually prone to the formation of a fracture line or preferred discontinuity (conditioned by the anisotropy of the urolithiasis)...
April 17, 2018: Actas Urologicas Españolas
Christophe Gaudet-Blavignac, Vasiliki Foufi, Eric Wehrli, Christian Lovis
Medical data is multimodal. In particular, it is composed of both structured data and narrative data (free text). Narrative data is a type of unstructured data that, although containing valuable semantic and conceptual information, is rarely reused. In order to assure interoperability of medical data, automatic annotation of free text with SNOMED CT concepts via Natural Language Processing (NLP) tools is proposed. This task is performed using a hybrid multilingual syntactic parser. A preliminary evaluation of the annotation shows encouraging results and confirms that semantic enrichment of patient-related narratives can be accomplished by hybrid NLP systems, heavily based on syntax and lexicosemantic resources...
2018: Studies in Health Technology and Informatics
Udo Hahn, Franz Matthies, Christina Lohr, Markus Löffler
We introduce 3000PA, a clinical document corpus composed of 3,000 EPRs from three different clinical sites, which will serve as the backbone of a national reference language resource for German clinical NLP. We outline its design principles, results from a medication annotation campaign and the evaluation of a first medication information extraction prototype using a subset of 3000PA.
2018: Studies in Health Technology and Informatics
Nishita Mehta, Anil Pandit
BACKGROUND: The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. PURPOSE: This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. DATA SOURCES: A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis...
June 2018: International Journal of Medical Informatics
Chia-Yen Chen, Phil H Lee, Victor M Castro, Jessica Minnier, Alexander W Charney, Eli A Stahl, Douglas M Ruderfer, Shawn N Murphy, Vivian Gainer, Tianxi Cai, Ian Jones, Carlos N Pato, Michele T Pato, Mikael Landén, Pamela Sklar, Roy H Perlis, Jordan W Smoller
Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al...
April 18, 2018: Translational Psychiatry
Nishant Kumar, Laura J Tafe, John H Higgins, Jason D Peterson, Francise Blumental de Abreu, Sophie J Deharvengt, Gregory J Tsongalis, Christopher I Amos, Saeed Hassanpour
OBJECTIVE: We aim to build an informatics methodology capable of identifying statistically significant associations between the clinical findings of non-small cell lung cancer (NSCLC) recorded in patient pathology reports and the various clinically actionable genetic mutations identified from next-generation sequencing (NGS) of patient tumor samples. METHODS: We built an information extraction and analysis pipeline to identify the associations between clinical findings in the pathology reports of patients and corresponding genetic mutations...
February 2018: Methods of Information in Medicine
Kristine E Lynch, Brian W Whitcomb, Scott L DuVall
When electronic health record (EHR) data are used, multiple approaches may be available for measuring the same variable, introducing potentially confounding factors. While additional information may be gleaned and residual confounding reduced through resource-intensive assessment methods such as natural language processing (NLP), whether the added benefits offset the added cost of the additional resources is not straightforward. We evaluated the implications of misclassification of a confounder when using EHRs...
2018: Perspectives in Health Information Management
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