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Retrieval-based learning

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https://www.readbyqxmd.com/read/28225448/predicting-hcahps-scores-from-hospitals-social-media-pages-a-sentiment-analysis
#1
John W Huppertz, Peter Otto
BACKGROUND: Social media is an important communication channel that can help hospitals and consumers obtain feedback about quality of care. However, despite the potential value of insight from consumers who post comments about hospital care on social media, there has been little empirical research on the relationship between patients' anecdotal feedback and formal measures of patient experience. PURPOSE: The aim of the study was to test the association between informal feedback posted in the Reviews section of hospitals' Facebook pages and scores on two global items from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, Overall Hospital Rating and Willingness to Recommend the Hospital...
February 22, 2017: Health Care Management Review
https://www.readbyqxmd.com/read/28209159/do-coursework-summative-assessments-predict-clinical-performance-a-systematic-review
#2
Rebecca Terry, Wayne Hing, Robin Orr, Nikki Milne
BACKGROUND: Two goals of summative assessment in health profession education programs are to ensure the robustness of high stakes decisions such as progression and licensing, and predict future performance. This systematic and critical review aims to investigate the ability of specific modes of summative assessment to predict the clinical performance of health profession education students. METHODS: PubMed, CINAHL, SPORTDiscus, ERIC and EMBASE databases were searched using key terms with articles collected subjected to dedicated inclusion criteria...
February 16, 2017: BMC Medical Education
https://www.readbyqxmd.com/read/28207384/supervised-learning-of-semantics-preserving-hash-via-deep-convolutional-neural-networks
#3
Huei-Fang Yang, Kevin Lin, Chu-Song Chen
This paper presents a simple yet effective supervised deep hash approach that constructs binary hash codes from labeled data for large-scale image search. We assume that the semantic labels are governed by several latent attributes with each attribute on or off, and classification relies on these attributes. Based on this assumption, our approach, dubbed supervised semantics-preserving deep hashing (SSDH), constructs hash functions as a latent layer in a deep network and the binary codes are learned by minimizing an objective function defined over classification error and other desirable hash codes properties...
February 9, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28134859/an-information-retrieval-approach-for-robust-prediction-of-road-surface-states
#4
Jae-Hyung Park, Kwanho Kim
Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods...
January 28, 2017: Sensors
https://www.readbyqxmd.com/read/28123033/the-caudate-nucleus-mediates-learning-of-stimulus-control-state-associations
#5
Yu-Chin Chiu, Jiefeng Jiang, Tobias Egner
: A longstanding dichotomy in cognitive psychology and neuroscience pits controlled, top-down driven behavior against associative, bottom-up driven behavior, where cognitive control processes allow us to override well-learned stimulus-response (S-R) associations. By contrast, some previous studies have raised the intriguing possibility of an integration between associative and controlled processing in the form of stimulus-control state (S-C) associations, the learned linkage of specific stimuli to particular control states, such as high attentional selectivity...
January 25, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28122063/flow-cytometric-single-cell-identification-of-populations-in-synthetic-bacterial-communities
#6
Peter Rubbens, Ruben Props, Nico Boon, Willem Waegeman
Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities...
2017: PloS One
https://www.readbyqxmd.com/read/28120406/generalization-and-maintenance-of-treatment-gains-in-primary-progressive-aphasia-ppa-a-systematic-review
#7
REVIEW
Inês Cadório, Marisa Lousada, Paula Martins, Daniela Figueiredo
BACKGROUND: Cognitive-linguistic treatments and interventions targeting communication have been developed within the context of primary progressive aphasia (PPA), however knowledge about the scope of generalization and maintenance of therapy gains considering PPA subtypes remains scarce and awaits systematic investigation. AIMS: To analyse the effects of semantic therapy on generalization and maintenance of treatment outcomes in individuals with PPA, considering its different subtypes...
January 24, 2017: International Journal of Language & Communication Disorders
https://www.readbyqxmd.com/read/28115219/combination-of-behaviorally-sub-effective-doses-of-glutamate-nmda-and-dopamine-d1-receptor-antagonists-impairs-executive-function
#8
Sagar J Desai, Brian L Allman, Nagalingam Rajakumar
Impairment of executive function is a core feature of schizophrenia. Preclinical studies indicate that injections of either N-methyl d-aspartate (NMDA) or dopamine D1 receptor blockers impair executive function. Despite the prevailing notion based on postmortem findings in schizophrenia that cortical areas have marked suppression of glutamate and dopamine, recent in vivo imaging studies suggest that abnormalities of these neurotransmitters in living patients may be quite subtle. Thus, we hypothesized that modest impairments in both glutamate and dopamine function can act synergistically to cause executive dysfunction...
April 14, 2017: Behavioural Brain Research
https://www.readbyqxmd.com/read/28115005/how-can-pharmacists-develop-patient-pharmacist-communication-skills-a-realist-review-protocol
#9
Aisling Kerr, Judith Strawbridge, Caroline Kelleher, Fien Mertens, Peter Pype, Myriam Deveugele, Teresa Pawlikowska
BACKGROUND: Good patient-pharmacist communication improves health outcomes. There is, however, room for improving pharmacists' communication skills. These develop through complex interactions during undergraduate pharmacy education, practice-based learning and continuing professional development. Research is needed to determine how best to approach teaching patient-pharmacist communication. METHODS: The aim of the research is to understand how educational interventions develop patient-pharmacist interpersonal communication skills produce their effects...
January 23, 2017: Systematic Reviews
https://www.readbyqxmd.com/read/28113853/instance-aware-hashing-for-multi-label-image-retrieval
#10
Hanjiang Lai, Pan Yan, Xiangbo Shu, Yunchao Wei, Shuicheng Yan
Similarity-preserving hashing is a commonly used method for nearest neighbour search in large-scale image retrieval. For image retrieval, deep-networks-based hashing methods are appealing since they can simultaneously learn effective image representations and compact hash codes. This paper focuses on deep-networks-based hashing for multi-label images, each of which may contain objects of multiple categories. In most existing hashing methods, each image is represented by one piece of hash code, which is referred to as semantic hashing...
March 22, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28113786/in-defense-of-locality-sensitive-hashing
#11
Kun Ding, Chunlei Huo, Bin Fan, Shiming Xiang, Chunhong Pan
Hashing-based semantic similarity search is becoming increasingly important for building large-scale content-based retrieval system. The state-of-the-art supervised hashing techniques use flexible two-step strategy to learn hash functions. The first step learns binary codes for training data by solving binary optimization problems with millions of variables, thus usually requiring intensive computations. Despite simplicity and efficiency, locality-sensitive hashing (LSH) has never been recognized as a good way to generate such codes due to its poor performance in traditional approximate neighbor search...
October 24, 2016: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28113708/supervised-matrix-factorization-hashing-for-cross-modal-retrieval
#12
Jun Tang, Ke Wang, Ling Shao
The target of cross-modal hashing is to embed heterogeneous multimedia data into a common low-dimensional Hamming space, which plays a pivotal part in multimedia retrieval due to the emergence of big multimodal data. Recently, matrix factorization has achieved great success in cross-modal hashing. However, how to effectively use label information and local geometric structure is still a challenging problem for these approaches. To address this issue, we propose a supervised crossmodal hashing method based on collective matrix factorization, which considers both the label consistency across different modalities and the local geometric consistency in each modality...
May 6, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28113699/elastic-functional-coding-of-riemannian-trajectories
#13
Rushil Anirudh, Pavan Turaga, Jingyong Su, Anuj Srivastava
Visual observations of dynamic phenomena, such as human actions, are often represented as sequences of smoothly-varying features . In cases where the feature spaces can be structured as Riemannian manifolds, the corresponding representations become trajectories on manifolds. Analysis of these trajectories is challenging due to non-linearity of underlying spaces and high-dimensionality of trajectories. In vision problems, given the nature of physical systems involved, these phenomena are better characterized on a low-dimensional manifold compared to the space of Riemannian trajectories...
May 6, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28113447/implementing-kernel-methods-incrementally-by-incremental-nonlinear-projection-trick
#14
Nojun Kwak
Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary...
May 20, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28113330/towards-retrieving-force-feedback-in-robotic-assisted-surgery-a-supervised-neuro-recurrent-vision-approach
#15
Angelica I Aviles Rivero, Samar M Alsaleh, James K Hahn, Alicia Casals
Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One of them is the lack of force feedback which restricts the surgeon's sense of touch and might reduce precision during a procedure. To overcome this limitation, we propose a novel force estimation approach that combines a vision based solution with supervised learning to estimate the applied force and provide the surgeon with a suitable representation of it...
December 15, 2016: IEEE Transactions on Haptics
https://www.readbyqxmd.com/read/28111643/mathematical-modeling-and-evaluation-of-human-motions-in-physical-therapy-using-mixture-density-neural-networks
#16
A Vakanski, J M Ferguson, S Lee
OBJECTIVE: The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement...
December 2016: J Physiother Phys Rehabil
https://www.readbyqxmd.com/read/28105915/spectral-consensus-strategy-for-accurate-reconstruction-of-large-biological-networks
#17
Séverine Affeldt, Nataliya Sokolovska, Edi Prifti, Jean-Daniel Zucker
BACKGROUND: The last decades witnessed an explosion of large-scale biological datasets whose analyses require the continuous development of innovative algorithms. Many of these high-dimensional datasets are related to large biological networks with few or no experimentally proven interactions. A striking example lies in the recent gut bacterial studies that provided researchers with a plethora of information sources. Despite a deeper knowledge of microbiome composition, inferring bacterial interactions remains a critical step that encounters significant issues, due in particular to high-dimensional settings, unknown gut bacterial taxa and unavoidable noise in sparse datasets...
December 13, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28103558/effective-multi-query-expansions-collaborative-deep-networks-for-robust-landmark-retrieval
#18
Yang Wang, Xuemin Lin, Lin Wu, Wenjie Zhang
Given a query photo issued by a user (q-user), the landmark retrieval is to return a set of photos with their landmarks similar to those of the query, while the existing studies on the landmark retrieval focus on exploiting geometries of landmarks for similarity matches between candidate photos and a query photo. We observe that the same landmarks provided by different users over social media community may convey different geometry information depending on the viewpoints and/or angles, and may, subsequently, yield very different results...
March 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28092544/discriminative-multi-view-interactive-image-re-ranking
#19
Jun Li, Chang Xu, Wankou Yang, Changyin Sun, Dacheng Tao
-Given unreliable visual patterns and insufficient query information, content-based image retrieval (CBIR) is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose Discriminative Multi-view INTeractive Image Re-ranking (DMINTIR), which integrates User Relevance Feedback (URF) capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28080119/the-role-of-episodic-context-in-retrieval-practice-effects
#20
Joshua W Whiffen, Jeffrey D Karpicke
The episodic context account of retrieval-based learning proposes that retrieval enhances subsequent retention because people must think back to and reinstate a prior learning context. Three experiments directly tested this central assumption of the context account. Subjects studied word lists and then either restudied the words under intentional learning conditions or made list discrimination judgments by indicating which list each word had occurred in originally. Subjects in both conditions experienced all items for the same amount of time, but subjects in the list discrimination condition were required to retrieve details about the original episodic context in which the words had occurred...
January 12, 2017: Journal of Experimental Psychology. Learning, Memory, and Cognition
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