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https://www.readbyqxmd.com/read/28230399/not-all-probabilities-are-equivalent-evidence-from-orientation-versus-spatial-probability-learning
#1
Syaheed B Jabar, Britt Anderson
Frequently targets are detected faster, probable locations searched earlier, and likely orientations estimated more precisely. Are these all consequences of a single, domain-general "attentional" effect? To examine this issue, participants were shown brief instances of spatial gratings, and were tasked to draw their location and orientation. Unknown to participants, either the location or orientation probability of these gratings were manipulated. While orientation probability affected the precision of orientation reports, spatial probability did not...
February 23, 2017: Journal of Experimental Psychology. Human Perception and Performance
https://www.readbyqxmd.com/read/28228630/social-activities-of-older-men-who-require-daily-support-and-the-purpose-of-such-activities
#2
Michiyo Hirano, Kazuko Saeki, Izumi Ueda, Hikaru Honda, Yoshiko Mizuno
Objectives The purpose of this study was to analyze the social activities of older men who require daily support, and to clarify the purpose of such activities, in order to develop effective living support and preventive long-term care service, suitable for this population.Methods Individual, semi-structured interviews were conducted with 17 older men. Data were analyzed using inductive and qualitative methods.Results Four categories of social activities were identified, and four categories of purposes of these social activities were extracted...
2017: [Nihon Kōshū Eisei Zasshi] Japanese Journal of Public Health
https://www.readbyqxmd.com/read/28227971/a-feature-exploration-methodology-for-learning-based-cuffless-blood-pressure-measurement-using-photoplethysmography
#3
Kefeng Duan, Zhiliang Qian, Mohamed Atef, Guoxing Wang, Kefeng Duan, Zhiliang Qian, Mohamed Atef, Guoxing Wang, Zhiliang Qian, Kefeng Duan, Guoxing Wang, Mohamed Atef
In this work, we propose a feature exploration method for learning-based cuffless blood pressure measurement. More specifically, to efficiently explore a large feature space from the photoplethysmography signal, we have applied several analytical techniques, including random error elimination, adaptive outlier removal, maximum information coefficient and Pearson's correlation coefficient based feature assessment methods. We evaluate fifty-seven possible feature candidates and propose three separate feature sets with each containing eleven features to predict the systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP), respectively...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227914/automated-classification-of-pathological-gait-after-stroke-using-ubiquitous-sensing-technology
#4
Elham Dolatabadi, Babak Taati, Alex Mihailidis, Elham Dolatabadi, Babak Taati, Alex Mihailidis, Babak Taati, Alex Mihailidis, Elham Dolatabadi
This study uses machine learning methods to distinguish between healthy and pathological gait. Examples of multi-dimensional pathological and normal gait sequences were collected from post-stroke and healthy individuals in a real clinical setting and with two Kinect sensors. The trajectories of rotational angle and global velocity of selected body joints (hips, spine, shoulders, neck, knees and ankles) over time formed the gait sequences. The combination of k nearest neighbor (kNN) and dynamic time warping (DTW) was used for classification...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227782/predicting-short-term-icu-outcomes-using-a-sequential-contrast-motif-based-classification-framework
#5
Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li
Critical ICU events like acute hypotension and septic shock are dangerous complications, leading to multiple organ failures and eventual death. Previously, pattern mining algorithms have been employed for extracting interesting rules in various clinical domains. However, the extracted rules are directly investigated by clinicians for diagnosing a disease. Towards this purpose, there is a need to develop advanced prediction models which integrate dynamic patterns to learn a patient's physiological condition...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227405/template-based-rodent-brain-extraction-and-atlas-mapping
#6
Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Jiaqi Zhang, Weimin Huang, Yuping Duan, Zhongkang Lu, Zhiping Lin, Su Huang
Accurate rodent brain extraction is the basic step for many translational studies using MR imaging. This paper presents a template based approach with multi-expert refinement to automatic rodent brain extraction. We first build the brain appearance model based on the learning exemplars. Together with the template matching, we encode the rodent brain position into the search space to reliably locate the rodent brain and estimate the rough segmentation. With the initial mask, a level-set segmentation and a mask-based template learning are implemented further to the brain region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227228/multi-view-non-negative-tensor-factorization-as-relation-learning-in-healthcare-data
#7
Hang Wu, May D Wang, Hang Wu, May D Wang, May D Wang, Hang Wu
Discovering patterns in co-occurrences data between objects and groups of concepts is a useful task in many domains, such as healthcare data analysis, information retrieval, and recommender systems. These relational representations come from objects' behaviors in different views, posing a challenging task of integrating information from these views to uncover the shared latent structures. The problem is further complicated by the high dimension of data and the large ratio of missing data. We propose a new paradigm of learning semantic relations using tensor factorization, by jointly factorizing multi-view tensors and searching for a consistent underlying semantic space across each views...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227163/maximum-correntropy-based-attention-gated-reinforcement-learning-designed-for-brain-machine-interface
#8
Hongbao Li, Fang Wang, Qiaosheng Zhang, Shaomin Zhang, Yiwen Wang, Xiaoxiang Zheng, Jose C Principe, Hongbao Li, Fang Wang, Qiaosheng Zhang, Shaomin Zhang, Yiwen Wang, Xiaoxiang Zheng, Jose C Principe, Yiwen Wang, Jose C Principe, Xiaoxiang Zheng, Qiaosheng Zhang, Shaomin Zhang, Hongbao Li, Fang Wang
Reinforcement learning is an effective algorithm for brain machine interfaces (BMIs) which interprets the mapping between neural activities with plasticity and the kinematics. Exploring large state-action space is difficulty when the complicated BMIs needs to assign credits over both time and space. For BMIs attention gated reinforcement learning (AGREL) has been developed to classify multi-actions for spatial credit assignment task with better efficiency. However, the outliers existing in the neural signals still make interpret the neural-action mapping difficult...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226933/development-of-artificial-tissue-like-structures-for-a-hybrid-epidural-anesthesia-simulator
#9
Benjamin Esterer, Johannes Razenbock, Marianne Hollensteiner, David Fuerst, Andreas Schrempf, Benjamin Esterer, Johannes Razenbock, Marianne Hollensteiner, David Fuerst, Andreas Schrempf, David Fuerst, Benjamin Esterer, Johannes Razenbock, Andreas Schrempf, Marianne Hollensteiner
Puncturing the epidural space and lumbar puncture are common procedures in anesthesia. They are carried out blind, where a needle is advanced from posterior between two adjacent vertebrae. Two different approaches are common practice for this technique, the midline and the paramedian one. The learning curve characteristics of both approaches significantly depends on the number of punctures carried out by a medical novice. For the training of these blind procedures a hybrid simulator requires artificial structures imitating the tissues which are penetrated by the needle...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226758/a-deep-bag-of-features-model-for-the-classification-of-melanomas-in-dermoscopy-images
#10
S Sabbaghi, M Aldeen, R Garnavi, S Sabbaghi, M Aldeen, R Garnavi, M Aldeen, S Sabbaghi, R Garnavi
Deep learning and unsupervised feature learning have received great attention in past years for their ability to transform input data into high level representations using machine learning techniques. Such interest has been growing steadily in the field of medical image diagnosis, particularly in melanoma classification. In this paper, a novel application of deep learning (stacked sparse auto-encoders) is presented for skin lesion classification task. The stacked sparse auto-encoder discovers latent information features in input images (pixel intensities)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226630/gaussian-process-dynamical-models-for-multimodal-affect-recognition
#11
Hernan F Garcia, Mauricio A Alvarez, Alvaro A Orozco, Hernan F Garcia, Mauricio A Alvarez, Alvaro A Orozco, Mauricio A Alvarez, Alvaro A Orozco, Hernan F Garcia
Affective computing systems has a great potential in applications for biofeedback systems and cognitive conductual therapies. Here, by analyzing the physiological behavior of a given subject, we can infer the affective state of an emotional process. Since, emotions can be modeled as dynamic manifestations of these signals, a continuous analysis in the valence/arousal space, brings more information of the affective state related to an emotional process. In this paper we propose a method for dynamic affect recognition from multimodal physiological signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226432/reinforcement-learning-for-stabilizing-an-inverted-pendulum-naturally-leads-to-intermittent-feedback-control-as-in-human-quiet-standing
#12
Kenjiro Michimoto, Yasuyuki Suzuki, Ken Kiyono, Yasushi Kobayashi, Pietro Morasso, Taishin Nomura, Kenjiro Michimoto, Yasuyuki Suzuki, Ken Kiyono, Yasushi Kobayashi, Pietro Morasso, Taishin Nomura, Ken Kiyono, Pietro Morasso, Kenjiro Michimoto, Yasushi Kobayashi, Yasuyuki Suzuki, Taishin Nomura
Intermittent feedback control for stabilizing human upright stance is a promising strategy, alternative to the standard time-continuous stiffness control. Here we show that such an intermittent controller can be established naturally through reinforcement learning. To this end, we used a single inverted pendulum model of the upright posture and a very simple reward function that gives a certain amount of punishments when the inverted pendulum falls or changes its position in the state space. We found that the acquired feedback controller exhibits hallmarks of the intermittent feedback control strategy, namely the action of the feedback controller is switched-off intermittently when the state of the pendulum is located near the stable manifold of the unstable saddle-type upright equilibrium of the inverted pendulum with no active control: this action provides an opportunity to exploit transiently converging dynamics toward the unstable upright position with no help of the active feedback control...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28222011/automatic-sleep-stage-classification-of-single-channel-eeg-by-using-complex-valued-convolutional-neural-network
#13
Junming Zhang, Yan Wu
Many systems are developed for automatic sleep stage classification. However, nearly all models are based on handcrafted features. Because of the large feature space, there are so many features that feature selection should be used. Meanwhile, designing handcrafted features is a difficult and time-consuming task because the feature designing needs domain knowledge of experienced experts. Results vary when different sets of features are chosen to identify sleep stages. Additionally, many features that we may be unaware of exist...
February 21, 2017: Biomedizinische Technik. Biomedical Engineering
https://www.readbyqxmd.com/read/28220333/developing-skilled-doctor-patient-communication-in-the-workplace-a-qualitative-study-of-the-experiences-of-trainees-and-clinical-supervisors
#14
Esther Giroldi, Wemke Veldhuijzen, Kristel Geelen, Jean Muris, Frits Bareman, Herman Bueving, Trudy van der Weijden, Cees van der Vleuten
To inform the development of recommendations to facilitate learning of skilled doctor-patient communication in the workplace, this qualitative study explores experiences of trainees and supervisors regarding how trainees learn communication and how supervisors support trainees' learning in the workplace. We conducted a qualitative study in a general practice training setting, triangulating various sources of data to obtain a rich understanding of trainees and supervisors' experiences: three focus group discussions, five discussions during training sessions and five individual interviews...
February 20, 2017: Advances in Health Sciences Education: Theory and Practice
https://www.readbyqxmd.com/read/28219731/time-place-learning-and-activity-profile-under-constant-light-and-constant-dark-in-zebrafish-danio-rerio
#15
Clarissa Ade Almeida Moura, Jéssica Polyana da Silva Lima, Vanessa Augusta Magalhães Silveira, Mário André Leocadio Miguel, Ana Carolina Luchiari
The ability to learn about the signs of variability in space and time is known as time place learning (TPL). To adjust their circadian rhythms, animals use stimuli that change regularly, such as the light-dark cycle, temperature, food availability or even social stimuli. Because light-dark cycle is the most important environmental temporal cue, we asked how a diurnal animal would perform TPL if this cue was removed. Zebrafish has been extensively studied in the chronobiology area due to it diurnal chronotype, thus, we studied the effects of constant light and constant dark on the time-place learning and activity profile in zebrafish...
February 17, 2017: Behavioural Processes
https://www.readbyqxmd.com/read/28217739/grounded-and-embodied-mathematical-cognition-promoting-mathematical-insight-and-proof-using-action-and-language
#16
Mitchell J Nathan, Candace Walkington
We develop a theory of grounded and embodied mathematical cognition (GEMC) that draws on action-cognition transduction for advancing understanding of how the body can support mathematical reasoning. GEMC proposes that participants' actions serve as inputs capable of driving the cognition-action system toward associated cognitive states. This occurs through a process of transduction that promotes valuable mathematical insights by eliciting dynamic depictive gestures that enact spatio-temporal properties of mathematical entities...
2017: Cogn Res Princ Implic
https://www.readbyqxmd.com/read/28215473/machine-learning-based-prediction-of-adverse-drug-effects-an-example-of-seizure-inducing-compounds
#17
Mengxuan Gao, Hideyoshi Igata, Aoi Takeuchi, Kaoru Sato, Yuji Ikegaya
Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning...
January 28, 2017: Journal of Pharmacological Sciences
https://www.readbyqxmd.com/read/28212704/neurochemical-differences-in-learning-and-memory-paradigms-among-rats-supplemented-with-anthocyanin-rich-blueberry-diets-and-exposed-to-acute-doses-of-56-fe-particles
#18
Shibu M Poulose, Bernard M Rabin, Donna F Bielinski, Megan E Kelly, Marshall G Miller, Nopporn Thanthaeng, Barbara Shukitt-Hale
The protective effects of anthocyanin-rich blueberries (BB) on brain health are well documented and are particularly important under conditions of high oxidative stress, which can lead to "accelerated aging." One such scenario is exposure to space radiation, consisting of high-energy and -charge particles (HZE), which are known to cause cognitive dysfunction and deleterious neurochemical alterations. We recently tested the behavioral and neurochemical effects of acute exposure to HZE particles such as (56)Fe, within 24-48h after exposure, and found that radiation primarily affects memory and not learning...
February 2017: Life Sciences in Space Research
https://www.readbyqxmd.com/read/28211048/the-assessment-of-knowledge-and-learning-in-competence-spaces-the-gain-loss-model-for-dependent-skills
#19
Pasquale Anselmi, Luca Stefanutti, Debora de Chiusole, Egidio Robusto
The gain-loss model (GaLoM) is a formal model for assessing knowledge and learning. In its original formulation, the GaLoM assumes independence among the skills. Such an assumption is not reasonable in several domains, in which some preliminary knowledge is the foundation for other knowledge. This paper presents an extension of the GaLoM to the case in which the skills are not independent, and the dependence relation among them is described by a well-graded competence space. The probability of mastering skill s at the pretest is conditional on the presence of all skills on which s depends...
February 17, 2017: British Journal of Mathematical and Statistical Psychology
https://www.readbyqxmd.com/read/28207397/stacked-learning-to-search-for-scene-labeling
#20
Feiyang Cheng, Xuming He, Hong Zhang
Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene labeling tasks. We design a simplified search process consisting of a sequence of ranking functions, which are learned based on a stacked learning strategy to prevent over-fitting...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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