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https://www.readbyqxmd.com/read/29149459/the-economic-impact-of-nursing
#1
EDITORIAL
Sharon M Brownie
Economics includes 'the condition of a region or group as regards material prosperity' (Oxford Dictionaries, 2017). The links between material prosperity versus poverty, health status and quality of life are well documented as are the devastating impacts of population disparities on the aforementioned indicators (Association of State and Territorial Health Officials, 2012). Poor health affects the ability of people to work, generate income and care for their families- a widely understood conundrum. In short, economic position impacts health status and health status impacts economic prosperity...
November 17, 2017: Journal of Clinical Nursing
https://www.readbyqxmd.com/read/29125126/improving-grn-re-construction-by-mining-hidden-regulatory-signals
#2
Ming Shi, Weiming Shen, Yanwen Chong, Hong-Qiang Wang
Inferring gene regulatory networks (GRNs) from gene expression data is an important but challenging issue in systems biology. Here, the authors propose a dictionary learning-based approach that aims to infer GRNs by globally mining regulatory signals, known or latent. Gene expression is often regulated by various regulatory factors, some of which are observed and some of which are latent. The authors assume that all regulators are unknown for a target gene and the expression of the target gene can be mapped into a regulatory space spanned by all the regulators...
December 2017: IET Systems Biology
https://www.readbyqxmd.com/read/29122011/entity-recognition-in-the-biomedical-domain-using-a-hybrid-approach
#3
Marco Basaldella, Lenz Furrer, Carlo Tasso, Fabio Rinaldi
BACKGROUND: This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. METHOD: The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only...
November 9, 2017: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29119146/4d-infant-cortical-surface-atlas-construction-using-spherical-patch-based-sparse-representation
#4
Zhengwang Wu, Gang Li, Yu Meng, Li Wang, Weili Lin, Dinggang Shen
The 4D infant cortical surface atlas with densely sampled time points is highly needed for neuroimaging analysis of early brain development. In this paper, we build the 4D infant cortical surface atlas firstly covering 6 postnatal years with 11 time points (i.e., 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, and 72 months), based on 339 longitudinal MRI scans from 50 healthy infants. To build the 4D cortical surface atlas, first, we adopt a two-stage groupwise surface registration strategy to ensure both longitudinal consistency and unbiasedness...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29109070/artificial-intelligence-learning-semantics-via-external-resources-for-classifying-diagnosis-codes-in-discharge-notes
#5
Chin Lin, Chia-Jung Hsu, Yu-Sheng Lou, Shih-Jen Yeh, Chia-Cheng Lee, Sui-Lung Su, Hsiang-Cheng Chen
BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). OBJECTIVE: Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes...
November 6, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/29104968/a-sparse-bayesian-learning-algorithm-for-white-matter-parameter-estimation-from-compressed-multi-shell-diffusion-mri
#6
Pramod Kumar Pisharady, Stamatios N Sotiropoulos, Guillermo Sapiro, Christophe Lenglet
We propose a sparse Bayesian learning algorithm for improved estimation of white matter fiber parameters from compressed (under-sampled q-space) multi-shell diffusion MRI data. The multi-shell data is represented in a dictionary form using a non-monoexponential decay model of diffusion, based on continuous gamma distribution of diffusivities. The fiber volume fractions with predefined orientations, which are the unknown parameters, form the dictionary weights. These unknown parameters are estimated with a linear un-mixing framework, using a sparse Bayesian learning algorithm...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29104279/two-stage-multi-task-representation-learning-for-synthetic-aperture-radar-sar-target-images-classification
#7
Xinzheng Zhang, Yijian Wang, Zhiying Tan, Dong Li, Shujun Liu, Tao Wang, Yongming Li
In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary is constructed based on the training subset. The second stage of the method is to perform target images classification based on the new dictionary, utilizing multi-task collaborative representation...
November 1, 2017: Sensors
https://www.readbyqxmd.com/read/29102809/spatio-temporal-modeling-of-connectome-scale-brain-network-interactions-via-time-evolving-graphs
#8
REVIEW
Jing Yuan, Xiang Li, Jinhe Zhang, Liao Luo, Qinglin Dong, Jinglei Lv, Yu Zhao, Xi Jiang, Shu Zhang, Wei Zhang, Tianming Liu
Many recent literature studies have revealed interesting dynamics patterns of functional brain networks derived from fMRI data. However, it has been rarely explored how functional networks spatially overlap (or interact) and how such connectome-scale network interactions temporally evolve. To explore these unanswered questions, this paper presents a novel framework for spatio-temporal modeling of connectome-scale functional brain network interactions via two main effective computational methodologies. First, to integrate, pool and compare brain networks across individuals and their cognitive states under task performances, we designed a novel group-wise dictionary learning scheme to derive connectome-scale consistent brain network templates that can be used to define the common reference space of brain network interactions...
November 9, 2017: NeuroImage
https://www.readbyqxmd.com/read/29100112/a-dictionary-learning-approach-for-human-sperm-heads-classification
#9
Fariba Shaker, S Amirhassan Monadjemi, Javad Alirezaie, Ahmad Reza Naghsh-Nilchi
BACKGROUND AND OBJECTIVE: To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes...
October 10, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29099718/paronymy-in-the-sublanguage-of-medicine-linguistic-and-linguo-didactic-aspects
#10
O Bieliaieva, Yu Lysanets, K Havrylieva, I Znamenska, I Rozhenko, N Nikolaieva
The present paper examines the phenomenon of paronymy in the sublanguage of medicine. The study of paronyms plays an important role in the development of terminological competence of future specialists in the field of medicine and healthcare. The authors emphasize the need to pay due attention to terminological paronyms when compiling teaching manuals and developing didactic materials in Latin for students of medical universities. The urgency of organizing the work with these lexical units is determined, on the one hand, by the propaedeutic objective - minimization of difficulties that students may encounter in dealing with special terminology in the process of educational and professional communication; on the other hand, the study of paronyms is aimed at expanding the active and passive vocabulary of medical students...
October 2017: Georgian Medical News
https://www.readbyqxmd.com/read/29094759/taxonomy-and-structure-of-the-romanian-personality-lexicon
#11
Vlad Burtăverde, Boele De Raad
We identified 1746 personality-relevant trait-adjectives in a Romanian dictionary, of which 412 were classified as descriptors of dispositions by 10 judges. Self-ratings were collected from 515 participants on those 412 adjectives, and the ratings were factored using principal components analysis. Solutions with different numbers of factors were analysed. The two- and three-factor solutions, respectively, confirmed the Big Two and Big Three of personality traits. A five-factor solution reflected the Big Five model with a fifth factor emphasising Rebelliousness versus Conventionality...
November 2, 2017: International Journal of Psychology: Journal International de Psychologie
https://www.readbyqxmd.com/read/29092588/using-self-organizing-maps-to-classify-humpback-whale-song-units-and-quantify-their-similarity
#12
Jenny A Allen, Anita Murray, Michael J Noad, Rebecca A Dunlop, Ellen C Garland
Classification of vocal signals can be undertaken using a wide variety of qualitative and quantitative techniques. Using east Australian humpback whale song from 2002 to 2014, a subset of vocal signals was acoustically measured and then classified using a Self-Organizing Map (SOM). The SOM created (1) an acoustic dictionary of units representing the song's repertoire, and (2) Cartesian distance measurements among all unit types (SOM nodes). Utilizing the SOM dictionary as a guide, additional song recordings from east Australia were rapidly (manually) transcribed...
October 2017: Journal of the Acoustical Society of America
https://www.readbyqxmd.com/read/29092410/extended-dynamic-mode-decomposition-with-dictionary-learning-a-data-driven-adaptive-spectral-decomposition-of-the-koopman-operator
#13
Qianxiao Li, Felix Dietrich, Erik M Bollt, Ioannis G Kevrekidis
Numerical approximation methods for the Koopman operator have advanced considerably in the last few years. In particular, data-driven approaches such as dynamic mode decomposition (DMD)(51) and its generalization, the extended-DMD (EDMD), are becoming increasingly popular in practical applications. The EDMD improves upon the classical DMD by the inclusion of a flexible choice of dictionary of observables which spans a finite dimensional subspace on which the Koopman operator can be approximated. This enhances the accuracy of the solution reconstruction and broadens the applicability of the Koopman formalism...
October 2017: Chaos
https://www.readbyqxmd.com/read/29081401/inadequate-drug-prescribing-comparison-of-inappropriate-drug-rates-at-the-end-of-a-geriatric-short-stay-service-with-three-prescribing-tools
#14
Jean-Luc Fanon, Sandra Dechavigny, Moustapha Dramé, Lidvine Godaert
To compare the proportion of prescriptions containing at least one inappropriate drug, as identified using three tools for optimizing drug prescriptions in the elderly. Cross-sectional, observational study based on the analysis of prescriptions of patients discharged between 1 September and 31 October 2014 in a short-stay geriatrics unit at the Louis Domergue de Trinité Hospital in Martinique (France). Each prescription was analysed using 3 tools, namely one for general medicine (Vidal © drug dictionary) and two tools specifically designed for geriatrics (the Laroche list of potentially inappropriate medications, and the STOPP-START toolkit)...
October 27, 2017: Gériatrie et Psychologie Neuropsychiatrie du Vieillissement
https://www.readbyqxmd.com/read/29077928/complexity-of-work-and-incident-cognitive-impairment-in-puerto-rican-older-adults
#15
Ross Andel, Ana Luisa Dávila-Roman, Catherine Grotz, Brent J Small, Kyriakos S Markides, Michael Crowe, Shevaun Neupert
Objective: We investigated complexity of work in main occupation in relation to incident cognitive impairment in older Puerto Ricans. Method: A population-based sample of 1,673 adults age 60+ for the Puerto Rican Elderly: Health Conditions (PREHCO) study was used. Cognition was measured at baseline and 4 years later using the Mini-Mental Cabán (MMC), with scoring 1.5 SD below the MMC score adjusted for age, education, gender, and reading ability comprising cognitive impairment...
October 25, 2017: Journals of Gerontology. Series B, Psychological Sciences and Social Sciences
https://www.readbyqxmd.com/read/29070915/sentiment-analysis-of-political-communication-combining-a-dictionary-approach-with-crowdcoding
#16
Martin Haselmayer, Marcelo Jenny
Sentiment is important in studies of news values, public opinion, negative campaigning or political polarization and an explosive expansion of digital textual data and fast progress in automated text analysis provide vast opportunities for innovative social science research. Unfortunately, tools currently available for automated sentiment analysis are mostly restricted to English texts and require considerable contextual adaption to produce valid results. We present a procedure for collecting fine-grained sentiment scores through crowdcoding to build a negative sentiment dictionary in a language and for a domain of choice...
2017: Quality & Quantity
https://www.readbyqxmd.com/read/29067333/accelerating-drug-development-for-alzheimer-s-disease-through-the-use-of-data-standards
#17
Jon Neville, Steve Kopko, Klaus Romero, Brian Corrigan, Bob Stafford, Elizabeth LeRoy, Steve Broadbent, Martin Cisneroz, Ethan Wilson, Eric Reiman, Hugo Vanderstichele, Stephen P Arnerić, Diane Stephenson
INTRODUCTION: The exceedingly high rate of failed trials in Alzheimer's disease (AD) calls for immediate attention to improve efficiencies and learning from past, ongoing, and future trials. Accurate, highly rigorous standardized data are at the core of meaningful scientific research. Data standards allow for proper integration of clinical data sets and represent the essential foundation for regulatory endorsement of drug development tools. Such tools increase the potential for success and accuracy of trial results...
June 2017: Alzheimer's & Dementia: Translational Research & Clinical Interventions
https://www.readbyqxmd.com/read/29066731/discriminative-prior-prior-image-constrained-compressed-sensing-reconstruction-for-low-dose-ct-imaging
#18
Yang Chen, Jin Liu, Lizhe Xie, Yining Hu, Huazhong Shu, Limin Luo, Libo Zhang, Zhiguo Gui, Gouenou Coatrieux
X-ray computed tomography (CT) has been widely used to provide patient-specific anatomical information in the forms of tissue attenuation. However, the cumulative radiation induced in CT scan has raised extensive concerns in recently years. How to maintain reconstruction image quality is a major challenge for low-dose CT (LDCT) imaging. Generally, LDCT imaging can be greatly improved by incorporating prior knowledge in some specific forms. A joint estimation framework termed discriminative prior-prior image constrained compressed sensing (DP-PICCS) reconstruction is proposed in this paper...
October 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29065467/adaptive-microwave-staring-correlated-imaging-for-targets-appearing-in-discrete-clusters
#19
Chao Tian, Zheng Jiang, Weidong Chen, Dongjin Wang
Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area...
October 21, 2017: Sensors
https://www.readbyqxmd.com/read/29060592/fast-dictionary-generation-and-searching-for-magnetic-resonance-fingerprinting
#20
Jun Xie, Mengye Lyu, Jian Zhang, Edward S Hui, Ed X Wu, Ze Wang
A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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