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https://www.readbyqxmd.com/read/28227852/non-linear-dynamic-modeling-of-glucose-in-type-1-diabetes-with-kernel-adaptive-filters
#1
Eleni I Georga, Jose C Principe, Demosthenes Polyzos, Dimitrios I Fotiadis, Eleni I Georga, Jose C Principe, Demosthenes Polyzos, Dimitrios I Fotiadis, Eleni I Georga, Demosthenes Polyzos, Jose C Principe, Dimitrios I Fotiadis
We propose a non-linear recursive solution to the problem of short-term prediction of glucose in type 1 diabetes. The Fixed Budget Quantized Kernel Least Mean Square (QKLMS-FB) algorithm is employed to construct a univariate model of subcutaneous glucose concentration, which: (i) handles nonlinearities by transforming the input space into a high-dimensional Reproducing Kernel Hilbert Space and, (ii) finds a sparse solution by retaining a representative subset of the training input vectors. The dataset comes from the continuous multi-day recordings of 15 type 1 patients in free-living conditions...
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
#2
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/28226976/thorax-disease-diagnosis-using-deep-convolutional-neural-network
#3
Jie Chen, Xianbiao Qi, Osmo Tervonen, Olli Silven, Guoying Zhao, Matti Pietikainen, Jie Chen, Xianbiao Qi, Osmo Tervonen, Olli Silven, Guoying Zhao, Matti Pietikainen, Osmo Tervonen, Xianbiao Qi, Jie Chen, Matti Pietikainen, Olli Silven, Guoying Zhao
Computer aided diagnosis (CAD) is an important issue, which can significantly improve the efficiency of doctors. In this paper, we propose a deep convolutional neural network (CNN) based method for thorax disease diagnosis. We firstly align the images by matching the interest points between the images, and then enlarge the dataset by using Gaussian scale space theory. After that we use the enlarged dataset to train a deep CNN model and apply the obtained model for the diagnosis of new test data. Our experimental results show our method achieves very promising results...
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
#4
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/28226864/the-influence-of-the-pre-stimulation-neural-state-on-the-post-stimulation-neural-dynamics-via-distributed-microstimulation-of-the-hippocampus
#5
Mark J Connolly, Robert E Gross, Babak Mahmoudi, Mark J Connolly, Robert E Gross, Babak Mahmoudi, Mark J Connolly, Robert E Gross, Babak Mahmoudi
In this study we investigated how the neural state influences how the brain responds to electrical stimulation using a 16-channel microelectrode array with 8 stimulation and recording channels implanted in the rat hippocampus. In two experiments we identified the stimulation threshold at which the brain changes to an afterdischarge state. In one experiment a range of suprathreshold stimulations were applied, and in another the stimulation was not changed. The neural state was measured by the power spectral density prior to stimulation...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226754/pixel-based-skin-segmentation-in-psoriasis-images
#6
Y George, M Aldeen, R Garnavi, Y George, M Aldeen, R Garnavi, M Aldeen, Y George, R Garnavi
In this paper, we present a detailed comparison study of skin segmentation methods for psoriasis images. Different techniques are modified and then applied to a set of psoriasis images acquired from the Royal Melbourne Hospital, Melbourne, Australia, with aim of finding the best technique suited for application to psoriasis images. We investigate the effect of different colour transformations on skin detection performance. In this respect, explicit skin thresholding is evaluated with three different decision boundaries (CbCr, HS and rgHSV)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226746/artery-vein-classification-of-retinal-blood-vessels-using-feature-selection
#7
Vishal Vijayakumar, Dara D Koozekanani, Robert White, James Kohler, Sohini Roychowdhury, Keshab K Parhi, Vishal Vijayakumar, Dara D Koozekanani, Robert White, James Kohler, Sohini Roychowdhury, Keshab K Parhi, James Kohler, Keshab K Parhi, Vishal Vijayakumar, Sohini Roychowdhury, Robert White, Dara D Koozekanani
Automated classification of retinal vessels in fundus images is the first step towards measurement of retinal characteristics that can be used to screen and diagnose vessel abnormalities for cardiovascular and retinal disorders. This paper presents a novel approach to vessel classification to compute the artery/vein ratio (AVR) for all blood vessel segments in the fundus image. The features extracted are then subjected to a selection procedure using Random Forests (RF) where the features that contribute most to classification accuracy are chosen as input to a polynomial kernel Support Vector Machine (SVM) classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28224488/hmms-in-protein-fold-classification
#8
Christos Lampros, Costas Papaloukas, Themis Exarchos, Dimitrios I Fotiadis
The limitation of most HMMs is their inherent high dimensionality. Therefore we developed several variations of low complexity models that can be applied even to protein families with a few members. In this chapter we present these variations. All of them include the use of a hidden Markov model (HMM), with a small number of states (called reduced state-space HMM), which is trained with both amino acid sequence and secondary structure of proteins whose 3D structure is known and it is used for protein fold classification...
2017: Methods in Molecular Biology
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
#9
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/28219745/interactive-exploration-for-continuously-expanding-neuron-databases
#10
Zhongyu Li, Dimitris N Metaxas, Aidong Lu, Shaoting Zhang
This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to associate neuronal morphologies with their functional properties. We design a coarse-to-fine framework for efficient and effective data retrieval from large-scale neuron databases. In the coarse-level, for efficiency in large-scale, we employ a binary coding method to compress morphological features into binary codes of tens of bits...
February 17, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28219726/diagnostic-value-of-sleep-stage-dissociation-as-visualized-on-a-2-dimensional-sleep-state-space-in-human-narcolepsy
#11
Anders Vinther Olsen, Jens Stephansen, Eileen Leary, Paul E Peppard, Hong Sheungshul, Poul Jenum, Helge Sorensen, Emmanuel Mignot
BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized that sleep stage dissociations can be objectively detected through the analysis of nocturnal Polysomnography (PSG) data, and that those affecting REM sleep can be used as a diagnostic feature for narcolepsy. NEW METHOD: A Linear Discriminant Analysis (LDA) model using 38 features extracted from EOG, EMG and EEG was used in control subjects to select features differentiating wake, stage N1, N2, N3 and REM sleep...
February 17, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28212082/semantic-highlight-retrieval-and-term-prediction
#12
Min Sun, Kuo-Hao Zeng, Yenchen Lin, Farhadi Ali
Due to the unprecedented growth of unedited videos, finding highlights relevant to a text query in a set of unedited videos has become increasingly important. We refer this task as semantic highlight retrieval and propose a query-dependent video representation for retrieving a variety of highlights. Our method consists of two parts: (1) "viralets", a mid-level representation bridging between semantic (Fig. 1(a)) and visual (Fig. 1(c)) spaces; (2) a novel Semantic-MODulation (SMOD) procedure to make viralets query-dependent (referred to as SMOD viralets)...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28195664/an-adaptive-model-for-rapid-and-direct-estimation-of-extravascular-extracellular-space-in-dynamic-contrast-enhanced-mri-studies
#13
Azimeh N V Dehkordi, Alireza Kamali-Asl, James R Ewing, Ning Wen, Indrin J Chetty, Hassan Bagher-Ebadian
Extravascular extracellular space (ve ) is a key parameter to characterize the tissue of cerebral tumors. This study introduces an artificial neural network (ANN) as a fast, direct, and accurate estimator of ve from a time trace of the longitudinal relaxation rate, ΔR1 (R1  = 1/T1 ), in DCE-MRI studies. Using the extended Tofts equation, a set of ΔR1 profiles was simulated in the presence of eight different signal to noise ratios. A set of gain- and noise-insensitive features was generated from the simulated ΔR1 profiles and used as the ANN training set...
February 14, 2017: NMR in Biomedicine
https://www.readbyqxmd.com/read/28195187/sensory-augmentation-integration-of-an-auditory-compass-signal-into-human-perception-of-space
#14
Frank Schumann, J Kevin O'Regan
Bio-mimetic approaches to restoring sensory function show great promise in that they rapidly produce perceptual experience, but have the disadvantage of being invasive. In contrast, sensory substitution approaches are non-invasive, but may lead to cognitive rather than perceptual experience. Here we introduce a new non-invasive approach that leads to fast and truly perceptual experience like bio-mimetic techniques. Instead of building on existing circuits at the neural level as done in bio-mimetics, we piggy-back on sensorimotor contingencies at the stimulus level...
February 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28188873/an-improved-fsl-first-pipeline-for-subcortical-gray-matter-segmentation-to-study-abnormal-brain-anatomy-using-quantitative-susceptibility-mapping-qsm
#15
Xiang Feng, Andreas Deistung, Michael G Dwyer, Jesper Hagemeier, Paul Polak, Jessica Lebenberg, Frédérique Frouin, Robert Zivadinov, Jürgen R Reichenbach, Ferdinand Schweser
Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T1-weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images...
February 7, 2017: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/28188012/-end-of-life-care-difficulties-in-intensive-care-units-the-nurses-perspective
#16
Juan Francisco Velarde-García, Raquel Luengo-González, Raquel González-Hervías, Sergio González-Cervantes, Beatriz Álvarez-Embarba, Domingo Palacios-Ceña
OBJECTIVE: To describe the difficulties perceived by nursing staff in the delivery of end-of-life care to critically ill patients within intensive care units (ICU). METHOD: A descriptive phenomenological qualitative study was performed. A purposeful and snowball sampling of nursing staff with at least 1 year's previous experience working in an ICU was conducted. Twenty-two participants were enrolled. Data collection strategies included in-depth unstructured and semi-structured interviews and researcher's field notes...
February 7, 2017: Gaceta Sanitaria
https://www.readbyqxmd.com/read/28173929/postflight-reconditioning-for-european-astronauts-a-case-report-of-recovery-after-six-months-in-space
#17
Nora Petersen, Gunda Lambrecht, Jonathan Scott, Natalie Hirsch, Maria Stokes, Joachim Mester
BACKGROUND: Postflight reconditioning of astronauts is understudied. Despite a rigorous, daily inflight exercise countermeasures programme during six months in microgravity (μG) on-board the International Space Station (ISS), physiological impairments occur and postflight reconditioning is still required on return to Earth. Such postflight programmes are implemented by space agency reconditioning specialists. Case Description and Assessments: A 38 year old male European Space Agency (ESA) crewmember's pre- and postflight (at six and 21 days after landing) physical performance from a six-month mission to ISS are described...
January 2017: Musculoskelet Sci Pract
https://www.readbyqxmd.com/read/28167399/adapted-mr-velocimetry-of-slow-liquid-flow-in-porous-media
#18
Li Huang, Gerd Mikolajczyk, Ekkehard Küstermann, Michaela Wilhelm, Stefan Odenbach, Wolfgang Dreher
MR velocimetry of liquid flow in opaque porous filters may play an important role in better understanding the mechanisms of deep bed filtration. With this knowledge, the efficiency of separating the suspended solid particles from the vertically flowing liquid can be improved, and thus a wide range of industrial applications such as wastewater treatment and desalination can be optimized. However, MR velocimetry is challenging for such studies due to the low velocities, the severe B0 inhomogeneity in porous structures, and the demand for high spatial resolution and an appropriate total measurement time during which the particle deposition will change velocities only marginally...
January 27, 2017: Journal of Magnetic Resonance
https://www.readbyqxmd.com/read/28166898/identification-of-the-emplacement-of-improvised-explosive-devices-by-experienced-mission-payload-operators
#19
Nathan J McNeese, Nancy J Cooke, Russell Branaghan, Ashley Knobloch, Amanda Taylor
Improvised Explosive Devices (IEDs) have become one of the deadliest threats to military personnel, resulting in over 50% of American combat casualties in Iraq and Afghanistan. Identification of IED emplacement is conducted by mission payload operators (MPOs). Yet, experienced MPOs are limited in number, making MPO training a critical intervention. In this article, we implement a Cognitive Engineering Based on Expert Skill methodology to better understand how experienced MPOs identify the emplacement of IEDs for the purposes of improving training...
April 2017: Applied Ergonomics
https://www.readbyqxmd.com/read/28166733/a-machine-learning-classifier-trained-on-cancer-transcriptomes-detects-nf1-inactivation-signal-in-glioblastoma
#20
Gregory P Way, Robert J Allaway, Stephanie J Bouley, Camilo E Fadul, Yolanda Sanchez, Casey S Greene
BACKGROUND: We have identified molecules that exhibit synthetic lethality in cells with loss of the neurofibromin 1 (NF1) tumor suppressor gene. However, recognizing tumors that have inactivation of the NF1 tumor suppressor function is challenging because the loss may occur via mechanisms that do not involve mutation of the genomic locus. Degradation of the NF1 protein, independent of NF1 mutation status, phenocopies inactivating mutations to drive tumors in human glioma cell lines. NF1 inactivation may alter the transcriptional landscape of a tumor and allow a machine learning classifier to detect which tumors will benefit from synthetic lethal molecules...
February 6, 2017: BMC Genomics
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