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https://www.readbyqxmd.com/read/28535144/can-hybrid-educational-activities-of-team-and-problem-based-learning-program-be-effective-for-japanese-medical-students
#1
Kentaro Iwata, Asako Doi
No abstract text is available yet for this article.
May 16, 2017: International Journal of Medical Education
https://www.readbyqxmd.com/read/28534800/a-deep-convolutional-neural-network-based-framework-for-automatic-fetal-facial-standard-plane-recognition
#2
Zhen Yu, Ee-Leng Tan, Dong Ni, Jing Qin, Siping Chen, Shenli Li, Baiying Lei, Tianfu Wang
Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, considerable effort has been devoted to FFSP recognition using various hand-crafted features, but the recognition performance is still unsatisfactory due to the high intra-class variation of FFSPs and the high degree of visual similarity between FFSPs and other non-FFSPs...
May 17, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28534789/boundary-eliminated-pseudoinverse-linear-discriminant-for-imbalanced-problems
#3
Yujin Zhu, Zhe Wang, Hongyuan Zha, Daqi Gao
Existing learning models for classification of imbalanced data sets can be grouped as either boundary-based or nonboundary-based depending on whether a decision hyperplane is used in the learning process. The focus of this paper is a new approach that leverages the advantage of both approaches. Specifically, our new model partitions the input space into three parts by creating two additional boundaries in the training process, and then makes the final decision based on a heuristic measurement between the test sample and a subset of selected training samples...
May 16, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28534788/rankmap-a-framework-for-distributed-learning-from-dense-data-sets
#4
Azalia Mirhoseini, Eva L Dyer, Ebrahim M Songhori, Richard Baraniuk, Farinaz Koushanfar
This paper introduces RankMap, a platform-aware end-to-end framework for efficient execution of a broad class of iterative learning algorithms for massive and dense data sets. Our framework exploits data structure to scalably factorize it into an ensemble of lower rank subspaces. The factorization creates sparse low-dimensional representations of the data, a property which is leveraged to devise effective mapping and scheduling of iterative learning algorithms on the distributed computing machines. We provide two APIs, one matrix-based and one graph-based, which facilitate automated adoption of the framework for performing several contemporary learning applications...
May 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28534781/reviving-the-two-state-markov-chain-approach
#5
Andrzej Mizera, Jun Pang, Qixia Yuan
Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such systems. However, for large PBNs, which often arise in systems biology, obtaining the steady-state distribution poses a significant challenge. In this paper, we revive the two-state Markov chain approach to solve this problem. This paper contributes in three aspects. First, we identify a problem of generating biased results with the approach and we propose a few heuristics to avoid such a pitfall...
May 16, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28534773/sparsity-based-color-image-super-resolution-via-exploiting-cross-channel-constraints
#6
Hojjat Mousavi, Vishal Monga
Sparsity constrained single image super-resolution (SR) has been of much recent interest. A typical approach involves sparsely representing patches in a low-resolution (LR) input image via a dictionary of example LR patches, and then using the coefficients of this representation to generate the highresolution (HR) output via an analogous HR dictionary. However, most existing sparse representation methods for super resolution focus on the luminance channel information and do not capture interactions between color channels...
May 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28534772/discriminative-transformation-for-multi-dimensional-temporal-sequences
#7
Bing Su, Xiaoqing Ding, Changsong Liu, Hao Wang, Ying Wu
Feature space transformation (FST) techniques have been widely studied for dimensionality reduction in vector-based feature space. However, these techniques are inapplicable to sequence data because the features in the same sequence are not independent. In this paper, we propose a method called max-min inter-sequence distance analysis (MMSDA) to transform features in sequences into a low-dimensional subspace such that different sequence classes are holistically separated. To utilize the temporal dependencies, MMSDA first aligns features in sequences from the same class to an adapted number of temporal states and then constructs the sequence class separability based on the statistics of these ordered states...
May 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28534767/domain-generalization-and-adaptation-using-low-rank-exemplar-svms
#8
Wen Li, Zheng Xu, Dong Xu, Dengxin Dai, Luc Van Gool
Domain adaptation between diverse source and target domains is a challenging research problem, especially in the real-world visual recognition tasks where the images and videos consist of significant variations in viewpoints, illuminations, qualities, etc. In this paper, we propose a new approach for domain generalization and domain adaptation based on exemplar SVMs. Specifically, we decompose the source domain into many subdomains, each of which contains only one positive training sample and all negative samples...
May 16, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28529875/advanced-magnetic-resonance-imaging-and-neuropsychological-assessment-for-detecting-brain-injury-in-a-prospective-cohort-of-university-amateur-boxers
#9
M G Hart, C R Housden, J Suckling, R Tait, A Young, U Müller, V F J Newcombe, I Jalloh, B Pearson, J Cross, R A Trivedi, J D Pickard, B J Sahakian, P J Hutchinson
BACKGROUND/AIM: The safety of amateur and professional boxing is a contentious issue. We hypothesised that advanced magnetic resonance imaging and neuropsychological testing could provide evidence of acute and early brain injury in amateur boxers. METHODS: We recruited 30 participants from a university amateur boxing club in a prospective cohort study. Magnetic resonance imaging (MRI) and neuropsychological testing was performed at three time points: prior to starting training; within 48 h following a first major competition to detect acute brain injury; and one year follow-up...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28528295/a-machine-learning-graph-based-approach-for-3d-segmentation-of-bruch-s-membrane-opening-from-glaucomatous-sd-oct-volumes
#10
Mohammad Saleh Miri, Michael D Abràmoff, Young H Kwon, Milan Sonka, Mona K Garvin
Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Measuring this structural parameter requires identification of BMO locations within spectral domain-optical coherence tomography (SD-OCT) volumes. While most automated approaches for segmentation of the BMO either segment the 2D projection of BMO points or identify BMO points in individual B-scans, in this work, we propose a machine-learning graph-based approach for true 3D segmentation of BMO from glaucomatous SD-OCT volumes...
May 6, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28526918/effect-of-problem-and-scripting-based-learning-on-spine-surgical-trainees-learning-outcomes
#11
Lin Cong, Qi Yan, Chenjing Sun, Yue Zhu, Guanjun Tu
PURPOSE: To assess the impact of problem and scripting-based learning (PSBL) on spine surgical trainees' learning outcomes. METHODS: 30 spine surgery postgraduate-year-1 residents (PGY-1s) from the First Hospital of China Medical University were randomly divided into two groups. The first group studied spine surgical skills and developed individual judgment under a conventional didactic model, whereas the PSBL group used PBL and Scripted model. A feedback questionnaire and the satisfaction of residents were evaluated by the first assistant surgeon immediately following each procedure...
May 19, 2017: European Spine Journal
https://www.readbyqxmd.com/read/28525928/-indicators-for-speech-comprehension-in-migrant-children-a-comparison-of-extreme-groups
#12
Christiane Kiese-Himmel, Herbert Poinstingl, Nicole von Steinbüchel
Objective Children with migrant background learning German as second language are frequently considered having problems in speech comprehension and speaking; nevertheless, it is very difficult to objectify that for young children. For this purpose risk-factors should be determined empirically. Material and Methods The study comprised 126 children from a developmental longitudinal study in 7 day-care centers in Frankfurt/M and Darmstadt. The sample was sorted into two extreme groups by their achievement in oral German language comprehension: criterion T-score ≥46=age appropriate (N=61) vs...
May 19, 2017: Laryngo- Rhino- Otologie
https://www.readbyqxmd.com/read/28525568/scenery-a-web-application-for-causal-network-reconstruction-from-cytometry-data
#13
Georgios Papoutsoglou, Giorgos Athineou, Vincenzo Lagani, Iordanis Xanthopoulos, Angelika Schmidt, Szabolcs Éliás, Jesper Tegnér, Ioannis Tsamardinos
Flow and mass cytometry technologies can probe proteins as biological markers in thousands of individual cells simultaneously, providing unprecedented opportunities for reconstructing networks of protein interactions through machine learning algorithms. The network reconstruction (NR) problem has been well-studied by the machine learning community. However, the potentials of available methods remain largely unknown to the cytometry community, mainly due to their intrinsic complexity and the lack of comprehensive, powerful and easy-to-use NR software implementations specific for cytometry data...
May 19, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28521065/eelab-an-innovative-educational-resource-in-occupational-medicine
#14
A Y Zhou, J Dodman, L Hussey, D Sen, C Rayner, N Zarin, R Agius
Background: Postgraduate education, training and clinical governance in occupational medicine (OM) require easily accessible yet rigorous, research and evidence-based tools based on actual clinical practice. Aims: To develop and evaluate an online resource helping physicians develop their OM skills using their own cases of work-related ill-health (WRIH). Methods: WRIH data reported by general practitioners (GPs) to The Health and Occupation Research (THOR) network were used to identify common OM clinical problems, their reported causes and management...
May 17, 2017: Occupational Medicine
https://www.readbyqxmd.com/read/28515699/active-involvement-of-end-users-when-developing-web-based-mental-health-interventions
#15
Derek de Beurs, Inge van Bruinessen, Janneke Noordman, Roland Friele, Sandra van Dulmen
BACKGROUND: Although many web-based mental health interventions are being released, the actual uptake by end users is limited. The marginal level of engagement of end users when developing these interventions is recognized as an important cause for uptake problems. In this paper, we offer our perceptive on how to improve user engagement. By doing so, we aim to stimulate a discourse on user involvement within the field of online mental health interventions. METHODS: We shortly describe three different methods (the expert-driven method, intervention mapping, and scrum) that were currently used to develop web-based health interventions...
2017: Frontiers in Psychiatry
https://www.readbyqxmd.com/read/28514914/using-action-learning-to-reduce-health-inequity-in-danish-municipalities
#16
Anna Paldam Folker, Sigurd Lauridsen
Purpose The aim of this study is to clarify how action learning can be used as a vehicle for promoting equal access to municipal health services for socially disadvantaged groups in a Danish context. It is the purpose of this paper to describe the methods for reducing health inequity developed in the study and to discuss how action learning methodologically contributed to achieving these results. Design/methodology/approach In the study, the front-line staff from 19 health and social service units in six different municipalities, in Denmark, each formed an action learning group to develop methods for reducing health inequity in a municipal health setting...
May 2, 2017: Leadership in Health Services
https://www.readbyqxmd.com/read/28513769/the-situation-of-nursing-education-in-latin-america-and-the-caribbean-towards-universal-health
#17
Silvia Helena De Bortoli Cassiani, Lynda Law Wilson, Sabrina de Souza Elias Mikael, Laura Morán Peña, Rosa Amarilis Zarate Grajales, Linda L McCreary, Lisa Theus, Maria Del Carmen Gutierrez Agudelo, Adriana da Silva Felix, Jacqueline Molina de Uriza, Nathaly Rozo Gutierrez
Objective: to assess the situation of nursing education and to analyze the extent to which baccalaureate level nursing education programs in Latin America and the Caribbean are preparing graduates to contribute to the achievement of Universal Health. Method: quantitative, descriptive/exploratory, cross-sectional study carried out in 25 countries. Results: a total of 246 nursing schools participated in the study. Faculty with doctoral level degrees totaled 31...
May 11, 2017: Revista Latino-americana de Enfermagem
https://www.readbyqxmd.com/read/28511125/the-many-facets-of-motor-learning-and-their-relevance-for-parkinson-s-disease
#18
REVIEW
Lucio Marinelli, Angelo Quartarone, Mark Hallett, Giuseppe Frazzitta, Maria Felice Ghilardi
The final goal of motor learning, a complex process that includes both implicit and explicit (or declarative) components, is the optimization and automatization of motor skills. Motor learning involves different neural networks and neurotransmitters systems depending on the type of task and on the stage of learning. After the first phase of acquisition, a motor skill goes through consolidation (i.e., becoming resistant to interference) and retention, processes in which sleep and long-term potentiation seem to play important roles...
April 9, 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28507452/consulted-ethical-problems-of-clinical-nursing-practice-perspective-of-faculty-members-in-japan
#19
Mari Tsuruwaka
BACKGROUND: There are several studies that have targeted student nurses, but few have clarified the details pertaining to the specific ethical problems in clinical practice with the viewpoint of the nursing faculty. This study was to investigate the ethical problems in clinical practice reported by student nurses to Japanese nursing faculty members for the purpose of improving ethics education in clinical practice. METHOD: The subjects comprised 705 nursing faculty members (we sent three questionnaires to one university) who managed clinical practice education at 235 Japanese nursing universities...
2017: BMC Nursing
https://www.readbyqxmd.com/read/28506904/ordinal-convolutional-neural-networks-for-predicting-rdoc-positive-valence-psychiatric-symptom-severity-scores
#20
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
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