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https://www.readbyqxmd.com/read/29165915/development-and-implementation-of-a-radiation-therapy-incident-learning-system-compatible-with-local-workflow-and-a-national-taxonomy
#1
Logan Montgomery, Palma Fava, Carolyn R Freeman, Tarek Hijal, Ciro Maietta, William Parker, John Kildea
PURPOSE: Collaborative incident learning initiatives in radiation therapy promise to improve and standardize the quality of care provided by participating institutions. However, the software interfaces provided with such initiatives must accommodate all participants and thus are not optimized for the workflows of individual radiation therapy centers. This article describes the development and implementation of a radiation therapy incident learning system that is optimized for a clinical workflow and uses the taxonomy of the Canadian National System for Incident Reporting - Radiation Treatment (NSIR-RT)...
November 22, 2017: Journal of Applied Clinical Medical Physics
https://www.readbyqxmd.com/read/29164340/correlation-filters-for-detection-of-cellular-nuclei-in-histopathology-images
#2
Asif Ahmad, Amina Asif, Nasir Rajpoot, Muhammad Arif, Fayyaz Ul Amir Afsar Minhas
Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now...
November 21, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/29163380/focused-review-cytotoxic-and-antioxidant-potentials-of-mangrove-derived-streptomyces
#3
REVIEW
Hooi-Leng Ser, Loh Teng-Hern Tan, Jodi Woan-Fei Law, Kok-Gan Chan, Acharaporn Duangjai, Surasak Saokaew, Priyia Pusparajah, Nurul-Syakima Ab Mutalib, Tahir Mehmood Khan, Bey-Hing Goh, Learn-Han Lee
Human life expectancy is rapidly increasing with an associated increasing burden of chronic diseases, such as neurodegenerative diseases and cancer. However, there is limited progress in finding effective treatment for these conditions. For this reason, members of the genus Streptomyces have been explored extensively over the past decades as these filamentous bacteria are highly efficient in producing bioactive compounds with human health benefits. Being ubiquitous in nature, streptomycetes can be found in both terrestrial and marine environments...
2017: Frontiers in Microbiology
https://www.readbyqxmd.com/read/29163121/joint-learning-of-binocularly-driven-saccades-and-vergence-by-active-efficient-coding
#4
Qingpeng Zhu, Jochen Triesch, Bertram E Shi
This paper investigates two types of eye movements: vergence and saccades. Vergence eye movements are responsible for bringing the images of the two eyes into correspondence, whereas saccades drive gaze to interesting regions in the scene. Control of both vergence and saccades develops during early infancy. To date, these two types of eye movements have been studied separately. Here, we propose a computational model of an active vision system that integrates these two types of eye movements. We hypothesize that incorporating a saccade strategy driven by bottom-up attention will benefit the development of vergence control...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/29163113/changes-of-attention-during-value-based-reversal-learning-are-tracked-by-n2pc-and-feedback-related-negativity
#5
Mariann Oemisch, Marcus R Watson, Thilo Womelsdorf, Anna Schubö
Previously learned reward values can have a pronounced impact, behaviorally and neurophysiologically, on the allocation of selective attention. All else constant, stimuli previously associated with a high value gain stronger attentional prioritization than stimuli previously associated with a low value. The N2pc, an ERP component indicative of attentional target selection, has been shown to reflect aspects of this prioritization, by changes of mean amplitudes closely corresponding to selective enhancement of high value target processing and suppression of high value distractor processing...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/29162279/clinical-decision-support-of-radiotherapy-treatment-planning-a-data-driven-machine-learning-strategy-for-patient-specific-dosimetric-decision-making
#6
Gilmer Valdes, Charles B Simone, Josephine Chen, Alexander Lin, Sue S Yom, Adam J Pattison, Colin M Carpenter, Timothy D Solberg
BACKGROUND AND PURPOSE: Clinical decision support systems are a growing class of tools with the potential to impact healthcare. This study investigates the construction of a decision support system through which clinicians can efficiently identify which previously approved historical treatment plans are achievable for a new patient to aid in selection of therapy. MATERIAL AND METHODS: Treatment data were collected for early-stage lung and postoperative oropharyngeal cancers treated using photon (lung and head and neck) and proton (head and neck) radiotherapy...
November 18, 2017: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology
https://www.readbyqxmd.com/read/29162003/feedforward-approximations-to-dynamic-recurrent-network-architectures
#7
Dylan R Muir
Recurrent neural network architectures can have useful computational properties, with complex temporal dynamics and input-sensitive attractor states. However, evaluation of recurrent dynamic architectures requires solving systems of differential equations, and the number of evaluations required to determine their response to a given input can vary with the input or can be indeterminate altogether in the case of oscillations or instability. In feedforward networks, by contrast, only a single pass through the network is needed to determine the response to a given input...
November 21, 2017: Neural Computation
https://www.readbyqxmd.com/read/29162002/encoding-time-in-feedforward-trajectories-of-a-recurrent-neural-network-model
#8
N F Hardy, Dean V Buonomano
Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing...
November 21, 2017: Neural Computation
https://www.readbyqxmd.com/read/29161845/spatially-implicit-modelling-of-disease-behaviour-interactions-in-the-context-of-non-pharmaceutical-interventions
#9
Notice Ringa, Chris T Bauch
Pair approximation models have been used to study the spread of infectious diseases in spatially distributed host populations, and to explore disease control strategies such as vaccination and case isolation. Here we introduce a pair approximation model of individual uptake of non-pharmaceutical interventions (NPIs) for an acute self-limiting infection, where susceptible individuals can learn the NPIs either from other susceptible individuals who are already practicing NPIs ("social learning"), or their uptake of NPIs can be stimulated by being neighbours of an infectious person ("exposure learning")...
April 1, 2018: Mathematical Biosciences and Engineering: MBE
https://www.readbyqxmd.com/read/29160478/family-resilience-and-chemical-dependency-perception-of-mental-health-professionals
#10
Sonia Regina Zerbetto, Sueli Aparecida Frari Galera, Bianca Oliveira Ruiz
OBJECTIVE: To learn the perception of health professionals from the Psychosocial Attention Center for Alcohol and Other Drugs regarding the resilience attributes that are critical to family members of psychoactive substance dependents. METHOD: A qualitative descriptive study conducted from February to May 2016, using a focus group technique for data collection. In total, 15 professionals participated in the study: 13 health professionals and two administrative professionals...
November 2017: Revista Brasileira de Enfermagem
https://www.readbyqxmd.com/read/29159999/-economies-of-experience-disambiguation-of-degraded-stimuli-leads-to-a-decreased-dispersion-of-eye-movement-patterns
#11
Magdalena Ewa Król, Michał Król
We demonstrate "economies of experience" in eye-movement patterns-that is, optimization of eye-movement patterns aimed at more efficient and less costly visual processing, similar to the priming-induced formation of sparser cortical representations or reduced reaction times. Participants looked at Mooney-type, degraded stimuli that were difficult to recognize without prior experience, but easily recognizable after exposure to their undegraded versions. As predicted, eye-movement dispersion, velocity, and the number of fixations decreased with each stimulus presentation...
November 20, 2017: Cognitive Science
https://www.readbyqxmd.com/read/29159798/tasks-determine-what-is-learned-in-visual-statistical-learning
#12
Timothy J Vickery, Su Hyoun Park, Jayesh Gupta, Marian E Berryhill
Visual statistical learning (VSL), the unsupervised learning of statistical contingencies across time and space, may play a key role in efficient and predictive encoding of the perceptual world. How VSL capabilities vary as a function of ongoing task demands is still poorly understood. VSL is modulated by selective attention and faces interference from some secondary tasks, but there is little evidence that the types of contingencies learned in VSL are sensitive to task demands. We found a powerful effect of task on what is learned in VSL...
November 20, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/29159278/comparative-evaluation-of-two-porcine-ex-vivo-models-for-training-in-endoscopic-ultrasound-guided-drainage-of-pancreatic-fluid-collections
#13
Frederick Moryoussef, Sarah Leblanc, Alice Bertucat, Arthur Laquiere, Emmanuel Coron, Luigi Mangialavori, Jean-Christophe Duchmann, Yann Le Baleur, Frederic Prat
Introduction:  EUS-guided cystoenterostomy (EUCE), a technique used for the drainage of pancreatic pseudocysts and peri-enteric collections, requires specific skills for which dedicated models are needed. Based on a compact EASIE model (Erlangen Active Simulator for Interventional Endoscopy), we developed two ex vivo porcine models of retrogastric cysts and evaluated learning performance within the frame of a structured training program. Material and methods:  The first model was made of porcine colon (i...
October 2017: Endoscopy International Open
https://www.readbyqxmd.com/read/29158838/crispr-genome-engineering-for-human-pluripotent-stem-cell-research
#14
REVIEW
Somali Chaterji, Eun Hyun Ahn, Deok-Ho Kim
The emergence of targeted and efficient genome editing technologies, such as repurposed bacterial programmable nucleases (e.g., CRISPR-Cas systems), has abetted the development of cell engineering approaches. Lessons learned from the development of RNA-interference (RNA-i) therapies can spur the translation of genome editing, such as those enabling the translation of human pluripotent stem cell engineering. In this review, we discuss the opportunities and the challenges of repurposing bacterial nucleases for genome editing, while appreciating their roles, primarily at the epigenomic granularity...
2017: Theranostics
https://www.readbyqxmd.com/read/29158061/machine-learning-in-radiology-applications-beyond-image-interpretation
#15
Paras Lakhani, Adam B Prater, R Kent Hutson, Kathy P Andriole, Keith J Dreyer, Jose Morey, Luciano M Prevedello, Toshi J Clark, J Raymond Geis, Jason N Itri, C Matthew Hawkins
Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside of image interpretation long before a fully functional "machine radiologist" is implemented in practice. Here, we describe an overview of machine learning, its application to radiology and other domains, and many cases of use that do not involve image interpretation...
November 16, 2017: Journal of the American College of Radiology: JACR
https://www.readbyqxmd.com/read/29156792/liquid-biopsy-in-colon-cancer-comparison-of-different-circulating-dna-extraction-systems-following-absolute-quantification-of-kras-mutations-using-intplex-allele-specific-pcr
#16
Vera Kloten, Nadine Rüchel, Nadina Ortiz Brüchle, Janina Gasthaus, Nils Freudenmacher, Florian Steib, Jolein Mijnes, Julian Eschenbruch, Marcel Binnebösel, Ruth Knüchel, Edgar Dahl
Non-invasive molecular analysis of circulating tumor DNA (ctDNA) is a promising application in personalized cancer management, although there is still much to learn about the biological characteristics of ctDNA. The present study compared absolute amounts of KRAS mutated ctDNA and total circulating cell-free DNA (cfDNA) in colorectal cancer (CRC) patients (n=50) from various stages and healthy controls (n=8) by Intplex allele-specific and digital droplet PCR. In addition, the impact of two prominent extraction techniques (silica-based membrane vs...
October 17, 2017: Oncotarget
https://www.readbyqxmd.com/read/29156276/formation-and-degradation-of-n-oxide-venlafaxine-during-ozonation-and-biological-post-treatment
#17
Ines Zucker, Hadas Mamane, Alon Riani, Igal Gozlan, Dror Avisar
While ozonation is considered an efficient treatment to eliminate trace organic compounds (TrOCs) from secondary wastewater effluents, the presence and persistence of transformation products (TPs) resulting from ozonation of TrOCs is a major concern that should be assessed prior to effluent discharge to the environment. Venlafaxine (VLX), an environmentally relevant tertiary amine-containing TrOC, was chosen as the model for this study. TP analysis confirmed that the lone electron pair of the non-protonated amine are the predominant site of oxidant attack, and therefore strongly affected by pH value and VLX speciation...
November 17, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/29155703/modeling-amyloid-%C3%AE-42-toxicity-and-neurodegeneration-in-adult-zebrafish-brain
#18
Prabesh Bhattarai, Alvin Kuriakose Thomas, Mehmet Ilyas Cosacak, Christos Papadimitriou, Violeta Mashkaryan, Yixin Zhang, Caghan Kizil
Alzheimer's disease (AD) is a debilitating neurodegenerative disease in which accumulation of toxic amyloid-β42 (Aβ42) peptides leads to synaptic degeneration, inflammation, neuronal death, and learning deficits. Humans cannot regenerate lost neurons in the case of AD in part due to impaired proliferative capacity of the neural stem/progenitor cells (NSPCs) and reduced neurogenesis. Therefore, efficient regenerative therapies should also enhance the proliferation and neurogenic capacity of NSPCs. Zebrafish (Danio rerio) is a regenerative organism, and we can learn the basic molecular programs with which we could design therapeutic approaches to tackle AD...
October 25, 2017: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/29154439/verbal-short-term-memory-shows-a-specific-association-with-receptive-but-not-productive-vocabulary-measures-in-down-syndrome
#19
S Majerus, K Barisnikov
BACKGROUND: Verbal short-term memory (STM) capacity has been considered to support vocabulary learning in typical children and adults, but evidence for this link is inconsistent for studies in individuals with Down syndrome (DS). The aim of this study was explore the role of processing demands on the association between verbal STM and vocabulary measures in DS, by comparing receptive vocabulary measures with high STM processing demands to productive vocabulary measures with low STM processing demands...
November 20, 2017: Journal of Intellectual Disability Research: JIDR
https://www.readbyqxmd.com/read/29153957/adaptive-neuro-heuristic-hybrid-model-for-fruit-peel-defects-detection
#20
Marcin Woźniak, Dawid Połap
Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the development of adaptive method based on fusion of proposed novel neural architecture and heuristic search into one co-working solution. We propose a developed neural network architecture that adapts to processed input co-working with heuristic method used to precisely detect areas of interest...
November 15, 2017: Neural Networks: the Official Journal of the International Neural Network Society
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