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Retrieval-based learning

Fernando Yepes-Calderon, Marvin D Nelson, J Gordon McComb
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and access it at a voxel level, decrypted and uncompressed that allows analytical capabilities while not perturbing the system's daily operation. Additionally, the strategy is secure and vendor independent. Cerebral ventricular volume is important for the diagnosis and treatment of many neurological disorders...
2018: PloS One
Ivo Kim Joore, Jan E A M van Bergen, Gerben Ter Riet, A van der Maat, N van Dijk
BACKGROUND: In the Netherlands, a substantial proportion of newly diagnosed HIV patients present late for care, therefore, we investigated the effectiveness of a blended educational programme for trainers of GPs designed to stimulate proactive HIV testing. METHODS: GP trainers at the Academic Medical Center in Amsterdam were invited to participate in a two days training programme incorporating evidence-based practice guidelines and multiple teaching strategies, including interactive lectures, discussion groups, e-learning and quality improvement targets...
March 7, 2018: BMC Family Practice
Nicolas Pavillon, Alison J Hobro, Shizuo Akira, Nicholas I Smith
We present a method enabling the noninvasive study of minute cellular changes in response to stimuli, based on the acquisition of multiple parameters through label-free microscopy. The retrieved parameters are related to different attributes of the cell. Morphological variables are extracted from quantitative phase microscopy and autofluorescence images, while molecular indicators are retrieved via Raman spectroscopy. We show that these independent parameters can be used to build a multivariate statistical model based on logistic regression, which we apply to the detection at the single-cell level of macrophage activation induced by lipopolysaccharide (LPS) exposure and compare their respective performance in assessing the individual cellular state...
March 6, 2018: Proceedings of the National Academy of Sciences of the United States of America
Tarek Amer, Kelly S Giovanello, Cheryl L Grady, Lynn Hasher
Older adults typically show poor associative memory performance relative to younger adults. This age-related effect, however, is mediated by the meaningfulness of the materials used, such that age differences are minimized with the use of information that is consistent with prior knowledge. While this effect has been interpreted as facilitative learning through schematic support, the role of memory retrieval on this effect has yet to be explored. Using an associative memory paradigm that varied the extent of controlled retrieval for previously studied meaningful or arbitrary associations, older and younger adults in the present study retrieved realistic and unrealistic grocery item prices in a speeded, or in a slow, more control-based retrieval condition...
February 2018: Psychology and Aging
Jin-Hui Wang, Shan Cui
The acquisition, integration and storage of exogenous associated signals are termed as associative learning and memory. The consequences and processes of associative thinking and logical reasoning based on these stored exogenous signals can be memorized as endogenous signals, which are essential for decision making, intention, and planning. Associative memory cells recruited in these primary and secondary associative memories are presumably the foundation for the brain to fulfill cognition events and emotional reactions in life, though the plasticity of synaptic connectivity and neuronal activity has been believed to be involved in learning and memory...
2018: F1000Research
Bin Liu, Yingming Li, Zenglin Xu
Multi-label learning is a common machine learning problem arising from numerous real-world applications in diverse fields, e.g, natural language processing, bioinformatics, information retrieval and so on. Among various multi-label learning methods, the matrix completion approach has been regarded as a promising approach to transductive multi-label learning. By constructing a joint matrix comprising the feature matrix and the label matrix, the missing labels of test samples are regarded as missing values of the joint matrix...
February 14, 2018: Neural Networks: the Official Journal of the International Neural Network Society
Xiaonan L Liu, Deborah H Tan, Lynne M Reder
Theoretical explanations of the testing effect (why people learn better from a test than a re-study) have largely focused on either the benefit of attempting to retrieve the answer or on the benefit of re-encoding the queried information after a successful retrieval. While a less parsimonious account, prior neuroimaging evidence has led us to postulate that both of these processes contribute to the benefit of testing over re-study. To provide further empirical support for our position, we recorded ERPs while subjects attempted to recall the second word of a pair when cued with the first...
February 20, 2018: Neuropsychologia
Somayeh Sharifi, Abbas Pakdel, Mansour Ebrahimi, James M Reecy, Samaneh Fazeli Farsani, Esmaeil Ebrahimie
Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way...
2018: PloS One
Chuanjun Liu, Chengli Xiao
The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented...
2018: Frontiers in Psychology
R D Dias, M C Ngo-Howard, M T Boskovski, M A Zenati, S J Yule
BACKGROUND: Surgeons in the operating theatre deal constantly with high-demand tasks that require simultaneous processing of a large amount of information. In certain situations, high cognitive load occurs, which may impact negatively on a surgeon's performance. This systematic review aims to provide a comprehensive understanding of the different methods used to assess surgeons' cognitive load, and a critique of the reliability and validity of current assessment metrics. METHODS: A search strategy encompassing MEDLINE, Embase, Web of Science, PsycINFO, ACM Digital Library, IEEE Xplore, PROSPERO and the Cochrane database was developed to identify peer-reviewed articles published from inception to November 2016...
February 21, 2018: British Journal of Surgery
Greg Huffman, Davood G Gozli, Bernhard Hommel, Jay Pratt
Voluntary action control is accomplished through anticipating that action's perceptual outcomes. Some evidence suggests that this is only true when responses are intention-based rather than stimulus-based and that this difference is evidence of different response modes. More recently, however, it has been shown that response-outcome retrieval effects can occur with stimulus-based responses, and that the retrieval depended on response selection efficiency as decreasing the response selection efficiency increased response-outcome retrieval (Gozli et al...
February 16, 2018: Psychological Research
Ajay Anand Kumar, Lut Van Laer, Maaike Alaerts, Amin Ardeshirdavani, Yves Moreau, Kris Laukens, Bart Loeys, Geert Vandeweyer, Inanc Birol
Motivation: Computational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrating Pubmed abstracts, Gene Ontology, Sequence similarities, Mammalian and Human Phenotype Ontology, Pathway, Interactions, Disease Ontology, Gene Association database and Human Genome Epidemiology database, into the prediction model.We explore and address effects of sparsity and inter-feature dependencies within annotation sources, and the impact of bias towards specific annotations...
February 14, 2018: Bioinformatics
P A Robinson-Drummer, T Chakraborty, N A Heroux, J B Rosen, M E Stanton
The context preexposure facilitation effect (CPFE) is a variant of contextual fear conditioning in which acquisition of the contextual representation and association of the retrieved contextual memory with an immediate foots-hock are separated by 24hrs. During the CPFE, learning- related expression patterns of the early growth response -1 gene (Egr-1) vary based on training phase and brain sub-region in adult and adolescent rats (Asok, Schreiber, Jablonski, Rosen, & Stanton, 2013; Shreiber et al., 2014; Chakraborty, Asok, Stanton, & Rosen, 2016)...
February 13, 2018: Neurobiology of Learning and Memory
T H Hu, L Wan, T A Liu, M W Wang, T Chen, Y H Wang
Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences...
December 2017: Fa Yi Xue za Zhi
Zhongyu Li, Erik Butler, Kang Li, Aidong Lu, Shuiwang Ji, Shaoting Zhang
Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i...
February 12, 2018: Neuroinformatics
Nasibeh Talebi, Ali Motie Nasrabadi, Iman Mohammad-Rezazadeh
Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output...
February 2018: Cognitive Neurodynamics
Marco Virgolin, Irma W E M van Dij, Jan Wiersma, Cécile M Ronckers, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A N Bosman
PURPOSE: The aim of this study is to establish the first step towards a novel and highly individualized 3D dose distribution reconstruction method, based on CT scans and organ delineations of recently treated patients. Specifically, the feasibility of automatically selecting the CT scan of a recently treated childhood cancer patient who is similar to a given historically treated child who suffered from Wilms' tumor is assessed. METHODS: A cohort of 37 recently treated children between 2 and 6 years old is considered...
February 12, 2018: Medical Physics
Nisreen I R Yassin, Shaimaa Omran, Enas M F El Houby, Hemat Allam
BACKGROUND AND OBJECTIVE: The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer. METHODS: The SR was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field...
March 2018: Computer Methods and Programs in Biomedicine
Ivonne Rudolph, Thorsten Schmidt, Tobias Wozniak, Thomas Kubin, Dana Ruetters, Jutta Huebner
BACKGROUND: Physical activity has positive effects on cancer patients. Dancing addresses diverse bio-psycho-social aspects. Our aim was to assess the evidence on ballroom dancing and to develop the setting for a pilot project. METHODS: We performed a systematic review, extracted the data and designed a pilot training based on standard curricula. We included cancer patients during or after therapy. Training duration was 90 min with one regular pause and individual pauses as needed...
February 8, 2018: Journal of Cancer Research and Clinical Oncology
Lijuan Huo, Rui Li, Pengyun Wang, Zhiwei Zheng, Juan Li
While the neural correlates of age-related decline in episodic memory have been the subject of much interest, the spontaneous functional architecture of the brain for various memory processes in elderly adults, such as immediate recall (IR) and delayed recall (DR), remains unclear. The present study thus examined the neural correlates of age-related decline of various memory processes. A total of 66 cognitively normal older adults (aged 60-80 years) participated in this study. Memory processes were measured using the Auditory Verbal Learning Test as well as resting-state brain images, which were analyzed using both regional homogeneity (ReHo) and correlation-based functional connectivity (FC) approaches...
2018: Frontiers in Aging Neuroscience
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