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https://www.readbyqxmd.com/read/29334640/not-single-brain-areas-but-a-network-is-involved-in-language-applications-in-presurgical-planning
#1
Razieh Alemi, Seyed Amir Hossein Batouli, Ebrahim Behzad, Mitra Ebrahimpoor, Mohammad Ali Oghabian
OBJECTIVES: Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential. PATIENTS AND METHODS: In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced...
January 10, 2018: Clinical Neurology and Neurosurgery
https://www.readbyqxmd.com/read/29328554/cross-mapping-of-nursing-care-terms-recorded-in-italian-hospitals-into-the-standardized-nnn-terminology
#2
Fabio D'Agostino, Valentina Zeffiro, Ercole Vellone, Davide Ausili, Romina Belsito, Antonella Leto, Rosaria Alvaro
PURPOSE: To evaluate if nursing diagnoses, interventions, and outcomes, as recorded by nurses in Italian hospitals, were semantically equivalent to the NANDA-I, NIC, and NOC (NNN) terminology. METHODS: A cross-mapping study using a multicenter design. Terms indicating nursing diagnoses, interventions, and outcomes were collected using the D-Catch instrument. Cross-mapping of these terms with NNN terminology was performed. FINDINGS: A sample of 137 nursing documentations was included...
January 12, 2018: International Journal of Nursing Knowledge
https://www.readbyqxmd.com/read/29324412/implicit-negative-sub-categorization-and-sink-diversion-for-object-detection
#3
Yu Li, Sheng Tang, Min Lin, Yongdong Zhang, Jintao Li, Shuicheng Yan
In this paper, we focus on improving the proposal classification stage in the object detection task and present implicit negative sub-categorization and sink diversion to lift the performance by strengthening loss function in this stage. First, based on the observation that the "background" class is generally very diverse and thus challenging to be handled as a single indiscriminative class in existing state-of-the-art methods, we propose to divide the background category into multiple implicit sub-categories to explicitly differentiate diverse patterns within it...
April 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/29322915/comparison-alignment-and-synchronization-of-cell-line-information-between-clo-and-efo
#4
Edison Ong, Sirarat Sarntivijai, Simon Jupp, Helen Parkinson, Yongqun He
BACKGROUND: The Experimental Factor Ontology (EFO) is an application ontology driven by experimental variables including cell lines to organize and describe the diverse experimental variables and data resided in the EMBL-EBI resources. The Cell Line Ontology (CLO) is an OBO community-based ontology that contains information of immortalized cell lines and relevant experimental components. EFO integrates and extends ontologies from the bio-ontology community to drive a number of practical applications...
December 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29316970/cuiless2016-a-clinical-corpus-applying-compositional-normalization-of-text-mentions
#5
John D Osborne, Matthew B Neu, Maria I Danila, Thamar Solorio, Steven J Bethard
BACKGROUND: Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the ability of the normalization process to express semantic meaning. We generated a freely available corpus using post-coordinated concepts without a defined set of relationships that we term "compositional concepts" to evaluate their use in clinical text...
January 10, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29304151/the-role-of-carboxy-terminal-cross-linking-telopeptide-of-type-i-collagen-dual-x-ray-absorptiometry-bone-strain-and-romberg-test-in-a-new-osteoporotic-fracture-risk-evaluation-a-proposal-from-an-observational-study
#6
Fabio M Ulivieri, Luca P Piodi, Enzo Grossi, Luca Rinaudo, Carmelo Messina, Anna P Tassi, Marcello Filopanti, Anna Tirelli, Francesco Sardanelli
The consolidated way of diagnosing and treating osteoporosis in order to prevent fragility fractures has recently been questioned by some papers, which complained of overdiagnosis and consequent overtreatment of this pathology with underestimating other causes of the fragility fractures, like falls. A new clinical approach is proposed for identifying the subgroup of patients prone to fragility fractures. This retrospective observational study was conducted from January to June 2015 at the Nuclear Medicine-Bone Metabolic Unit of the of the Fondazione IRCCS Ca' Granda, Milan, Italy...
2018: PloS One
https://www.readbyqxmd.com/read/29301337/organ-segmentation-in-poultry-viscera-using-rgb-d
#7
Mark Philip Philipsen, Jacob Velling Dueholm, Anders Jørgensen, Sergio Escalera, Thomas Baltzer Moeslund
We present a pattern recognition framework for semantic segmentation of visual structures, that is, multi-class labelling at pixel level, and apply it to the task of segmenting organs in the eviscerated viscera from slaughtered poultry in RGB-D images. This is a step towards replacing the current strenuous manual inspection at poultry processing plants. Features are extracted from feature maps such as activation maps from a convolutional neural network (CNN). A random forest classifier assigns class probabilities, which are further refined by utilizing context in a conditional random field...
January 3, 2018: Sensors
https://www.readbyqxmd.com/read/29260348/medical-image-retrieval-with-compact-binary-codes-generated-in-frequency-domain-using-highly-reactive-convolutional-features
#8
Jamil Ahmad, Khan Muhammad, Sung Wook Baik
Efficient retrieval of relevant medical cases using semantically similar medical images from large scale repositories can assist medical experts in timely decision making and diagnosis. However, the ever-increasing volume of images hinder performance of image retrieval systems. Recently, features from deep convolutional neural networks (CNN) have yielded state-of-the-art performance in image retrieval. Further, locality sensitive hashing based approaches have become popular for their ability to allow efficient retrieval in large scale datasets...
December 19, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/29248603/mixed-metaphors-electrophysiological-brain-responses-to-un-expected-concrete-and-abstract-prepositional-phrases
#9
Emily Zane, Valerie Shafer
Languages around the world use spatial terminology, like prepositions, to describe non-spatial, abstract concepts, including time (e.g., in the moment). The Metaphoric Mapping Theory explains this pattern by positing that a universal human cognitive process underlies it, whereby abstract concepts are conceptualized via the application of concrete, three-dimensional space onto abstract domains. The alternative view is that the use of spatial propositions in abstract phrases is idiomatic, and thus does not trigger metaphoric mapping...
December 14, 2017: Brain Research
https://www.readbyqxmd.com/read/29228203/in-vivo-cholinergic-basal-forebrain-atrophy-predicts-cognitive-decline-in-de-novo-parkinson-s-disease
#10
Nicola J Ray, Steven Bradburn, Christopher Murgatroyd, Umar Toseeb, Pablo Mir, George K Kountouriotis, Stefan J Teipel, Michel J Grothe
Cognitive impairments are a prevalent and disabling non-motor complication of Parkinson's disease, but with variable expression and progression. The onset of serious cognitive decline occurs alongside substantial cholinergic denervation, but imprecision of previously available techniques for in vivo measurement of cholinergic degeneration limit their use as predictive cognitive biomarkers. However, recent developments in stereotactic mapping of the cholinergic basal forebrain have been found useful for predicting cognitive decline in prodromal stages of Alzheimer's disease...
December 8, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/29221183/radial-gradient-and-radial-deviation-radiomic-features-from-pre-surgical-ct-scans-are-associated-with-survival-among-lung-adenocarcinoma-patients
#11
Ilke Tunali, Olya Stringfield, Albert Guvenis, Hua Wang, Ying Liu, Yoganand Balagurunathan, Philippe Lambin, Robert J Gillies, Matthew B Schabath
The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied...
November 10, 2017: Oncotarget
https://www.readbyqxmd.com/read/29203203/a-new-insight-into-sentence-comprehension-the-impact-of-word-associations-in-sentence-processing-as-shown-by-invasive-eeg-recording
#12
Elvira Khachatryan, Harm Brouwer, Willeke Staljanssens, Evelien Carrette, Alfred Meurs, Paul Boon, Dirk van Roost, Marc M Van Hulle
The effect of word association on sentence processing is still a matter of debate. Some studies observe no effect while others found a dependency on sentence congruity or an independent effect. In an attempt to separate the effects of sentence congruity and word association in the spatio-temporal domain, we jointly recorded scalp- and invasive-EEG (iEEG). The latter provides highly localized spatial (unlike scalp-EEG) and high temporal (unlike fMRI) resolutions. We recorded scalp- and iEEG in three patients with refractory epilepsy...
December 1, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/29197409/matching-disease-and-phenotype-ontologies-in-the-ontology-alignment-evaluation-initiative
#13
Ian Harrow, Ernesto Jiménez-Ruiz, Andrea Splendiani, Martin Romacker, Peter Woollard, Scott Markel, Yasmin Alam-Faruque, Martin Koch, James Malone, Arild Waaler
BACKGROUND: The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. RESULTS: Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track...
December 2, 2017: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29197241/iconicity-affects-children-s-comprehension-of-complex-sentences-the-role-of-semantics-clause-order-input-and-individual-differences
#14
Laura E de Ruiter, Anna L Theakston, Silke Brandt, Elena V M Lieven
Complex sentences involving adverbial clauses appear in children's speech at about three years of age yet children have difficulty comprehending these sentences well into the school years. To date, the reasons for these difficulties are unclear, largely because previous studies have tended to focus on only sub-types of adverbial clauses, or have tested only limited theoretical models. In this paper, we provide the most comprehensive experimental study to date. We tested four-year-olds, five-year-olds and adults on four different adverbial clauses (before, after, because, if) to evaluate four different theoretical models (semantic, syntactic, frequency-based and capacity-constrained)...
November 29, 2017: Cognition
https://www.readbyqxmd.com/read/29186846/dimension-reduction-aided-hyperspectral-image-classification-with-a-small-sized-training-dataset-experimental-comparisons
#15
Jinya Su, Dewei Yi, Cunjia Liu, Lei Guo, Wen-Hua Chen
Hyperspectral images (HSI) provide rich information which may not be captured by other sensing technologies and therefore gradually find a wide range of applications. However, they also generate a large amount of irrelevant or redundant data for a specific task. This causes a number of issues including significantly increased computation time, complexity and scale of prediction models mapping the data to semantics (e.g., classification), and the need of a large amount of labelled data for training. Particularly, it is generally difficult and expensive for experts to acquire sufficient training samples in many applications...
November 25, 2017: Sensors
https://www.readbyqxmd.com/read/29182714/two-critical-brain-networks-for-generation-and-combination-of-remote-associations
#16
David Bendetowicz, Marika Urbanski, Béatrice Garcin, Chris Foulon, Richard Levy, Marie-Laure Bréchemier, Charlotte Rosso, Michel Thiebaut de Schotten, Emmanuelle Volle
Recent functional imaging findings in humans indicate that creativity relies on spontaneous and controlled processes, possibly supported by the default mode and the fronto-parietal control networks, respectively. Here, we examined the ability to generate and combine remote semantic associations, in relation to creative abilities, in patients with focal frontal lesions. Voxel-based lesion-deficit mapping, disconnection-deficit mapping and network-based lesion-deficit approaches revealed critical prefrontal nodes and connections for distinct mechanisms related to creative cognition...
November 22, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/29175548/radiology-report-annotation-using-intelligent-word-embeddings-applied-to-multi-institutional-chest-ct-cohort
#17
Imon Banerjee, Matthew C Chen, Matthew P Lungren, Daniel L Rubin
We proposed an unsupervised hybrid method - Intelligent Word Embedding (IWE) that combines neural embedding method with a semantic dictionary mapping technique for creating a dense vector representation of unstructured radiology reports. We applied IWE to generate embedding of chest CT radiology reports from two healthcare organizations and utilized the vector representations to semi-automate report categorization based on clinically relevant categorization related to the diagnosis of pulmonary embolism (PE)...
November 23, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29174790/towards-measuring-the-semantic-capacity-of-a-physical-medium-demonstrated-with-elementary-cellular-automata
#18
Peter Dittrich
The organic code concept and its operationalization by molecular codes have been introduced to study the semiotic nature of living systems. This contribution develops further the idea that the semantic capacity of a physical medium can be measured by assessing its ability to implement a code as a contingent mapping. For demonstration and evaluation, the approach is applied to a formal medium: elementary cellular automata (ECA). The semantic capacity is measured by counting the number of ways codes can be implemented...
November 21, 2017: Bio Systems
https://www.readbyqxmd.com/read/29165372/pedestrian-detection-with-semantic-regions-of-interest
#19
Miao He, Haibo Luo, Zheng Chang, Bin Hui
For many pedestrian detectors, background vs. foreground errors heavily influence the detection quality. Our main contribution is to design semantic regions of interest that extract the foreground target roughly to reduce the background vs. foreground errors of detectors. First, we generate a pedestrian heat map from the input image with a full convolutional neural network trained on the Caltech Pedestrian Dataset. Next, semantic regions of interest are extracted from the heat map by morphological image processing...
November 22, 2017: Sensors
https://www.readbyqxmd.com/read/29159059/triangulation-of-language-cognitive-impairments-naming-errors-and-their-neural-bases-post-stroke
#20
Ajay D Halai, Anna M Woollams, Matthew A Lambon Ralph
In order to gain a better understanding of aphasia one must consider the complex combinations of language impairments along with the pattern of paraphasias. Despite the fact that both deficits and paraphasias feature in diagnostic criteria, most research has focused only on the lesion correlates of language deficits, with minimal attention on the pattern of patients' paraphasias. In this study, we used a data-driven approach (principal component analysis - PCA) to fuse patient impairments and their pattern of errors into one unified model of chronic post-stroke aphasia...
2018: NeuroImage: Clinical
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