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Learning methods

Irene Fondón, Auxiliadora Sarmiento, Ana Isabel García, María Silvestre, Catarina Eloy, António Polónia, Paulo Aguiar
Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images...
March 8, 2018: Computers in Biology and Medicine
Han Liu, Xianchao Zhang, Xiaotong Zhang
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good...
February 27, 2018: Neural Networks: the Official Journal of the International Neural Network Society
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
Kenzie A Cameron, Elaine R Cohen, Joelle R Hertz, Diane B Wayne, Debi Mitra, Jeffrey H Barsuk
OBJECTIVES: The aims of the study were to identify perceived barriers and facilitators to central venous catheter (CVC) insertion among healthcare providers and to understand the extent to which an existing Simulation-Based Mastery Learning (SBML) program may address barriers and leverage facilitators. METHODS: Providers participating in a CVC insertion SBML train-the-trainer program, in addition to intensive care unit nurse managers, were purposively sampled from Veterans Administration Medical Centers located in geographically diverse areas...
March 14, 2018: Journal of Patient Safety
Paulina Duckic, Robert B Hayes
Buildup factors are dimensionless multiplicative factors required by the point kernel method to account for scattered radiation through a shielding material. The accuracy of the point kernel method is strongly affected by the correspondence of analyzed parameters to experimental configurations, which is attempted to be simplified here. The point kernel method has not been found to have widespread practical use for neutron shielding calculations due to the complex neutron transport behavior through shielding materials (i...
March 14, 2018: Health Physics
Scott W Paine, James R Fienup
For large amounts of wavefront error, gradient-based optimization methods for image-based wavefront sensing are unlikely to converge when the starting guess for the wavefront differs greatly from the true wavefront. We use machine learning operating on a point-spread function to determine a good initial estimate of the wavefront. We show that our trained convolutional neural network provides good initial estimates in the presence of simulated detector noise and is more effective than using many random starting guesses for large amounts of wavefront error...
March 15, 2018: Optics Letters
A V Dolzhich, S E Avetisov
PURPOSE: to assess the neurophysiological effect and clinical effectiveness of transcranial direct current stimulation in combination with drug therapy in amblyopic children. MATERIAL AND METHODS: The study involved 32 healthy children in the age of 5-12 years and 97 patients of the same age with refractive strabismic amblyopia. All study subjects underwent standard examination including ophthalmological (visometry, refractometry in normal conditions and in cycloplegia, biomicroscopy, ophthalmoscopy, type of vision), neurophysiological methods (determination of retinal electric sensitivity threshold, electric lability of optic nerve, amplitude and latency period of visual evoked potentials, electroencephalogram wave amplitudes, localization of peak electrical activity area of the cerebral cortex), assessment of neuropsychic development and estimation of mental development coefficient with age tests...
2018: Vestnik Oftalmologii
Sarthak Ghosh, Lauren Winston, Nishant Panchal, Philippe Kimura-Thollander, Jeff Hotnog, Douglas Cheong, Gabriel Reyes, Gregory D Abowd
The proliferation of high resolution and affordable virtual reality (VR) headsets is quickly making room-scale VR experiences available in our homes. Most VR experiences strive to achieve complete immersion by creating a disconnect from the real world. However, due to the lack of a standardized notification management system and minimal context awareness in VR, an immersed user may face certain situations such as missing an important phone call (digital scenario), tripping over wandering pets (physical scenario), or losing track of time (temporal scenario)...
April 2018: IEEE Transactions on Visualization and Computer Graphics
Wei Wang, Yan Yan, Feiping Nie, Shuicheng Yan, Nicu Sebe
Graph-based dimensionality reduction techniques have been widely and successfully applied to clustering and classification tasks. The basis of these algorithms is the constructed graph which dictates their performance. In general, the graph is defined by the input affinity matrix. However, the affinity matrix derived from the data is sometimes suboptimal for dimension reduction as the data used are very noisy. To address this issue, we propose the projective unsupervised flexible embedding models with optimal graph (PUFE-OG)...
June 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
F Mushtaq, C O'Driscoll, Fct Smith, D Wilkins, N Kapur, R Lawton
Background Confidential reporting systems play a key role in capturing information about adverse surgical events. However, the value of these systems is limited if the reports that are generated are not subjected to systematic analysis. The aim of this study was to provide the first systematic analysis of data from a novel surgical confidential reporting system to delineate contributory factors in surgical incidents and document lessons that can be learned. Methods One-hundred and forty-five patient safety incidents submitted to the UK Confidential Reporting System for Surgery over a 10-year period were analysed using an adapted version of the empirically-grounded Yorkshire Contributory Factors Framework...
March 15, 2018: Annals of the Royal College of Surgeons of England
Veronica T Rowe, Marsha Neville
Task-oriented training is a contemporary intervention based on behavioral neuroscience and recent models of motor learning. It can logically be guided by the theory of occupational adaptation. This report presents the perceptions of four participants who underwent task-oriented training at home (TOTE Home) for upper extremity hemiparesis following a stroke. Guided by principles of motor learning and the theory of occupational adaptation, a directed content analysis was used with field notes recorded during the TOTE Home...
March 1, 2018: OTJR: Occupation, Participation and Health
David Haro Alonso, Miles N Wernick, Yongyi Yang, Guido Germano, Daniel S Berman, Piotr Slomka
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR). We demonstrated an approach to visually convey the reasoning behind a patient's risk to provide insight to clinicians beyond that of a "black box." METHODS: We trained multiple models using 122 potential clinical predictors (features) for 8321 patients, including 551 cases of subsequent cardiac death...
March 14, 2018: Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology
Ruobing Huang, Ana Namburete, Alison Noble
We present a general framework for automatic segmentation of fetal brain structures in ultrasound images inspired by recent advances in machine learning. The approach is based on a region descriptor that characterizes the shape and local intensity context of different neurological structures without explicit models. To validate our framework, we present experiments to segment two fetal brain structures of clinical importance that have quite different ultrasonic appearances-the corpus callosum (CC) and the choroid plexus (CP)...
January 2018: Journal of Medical Imaging
Paul D Marasco, Jacqueline S Hebert, Jon W Sensinger, Courtney E Shell, Jonathon S Schofield, Zachary C Thumser, Raviraj Nataraj, Dylan T Beckler, Michael R Dawson, Dan H Blustein, Satinder Gill, Brett D Mensh, Rafael Granja-Vazquez, Madeline D Newcomb, Jason P Carey, Beth M Orzell
To effortlessly complete an intentional movement, the brain needs feedback from the body regarding the movement's progress. This largely nonconscious kinesthetic sense helps the brain to learn relationships between motor commands and outcomes to correct movement errors. Prosthetic systems for restoring function have predominantly focused on controlling motorized joint movement. Without the kinesthetic sense, however, these devices do not become intuitively controllable. We report a method for endowing human amputees with a kinesthetic perception of dexterous robotic hands...
March 14, 2018: Science Translational Medicine
Michelle Livne, Jens K Boldsen, Irene K Mikkelsen, Jochen B Fiebach, Jan Sobesky, Kim Mouridsen
BACKGROUND AND PURPOSE: Stroke imaging is pivotal for diagnosis and stratification of patients with acute ischemic stroke to treatment. The potential of combining multimodal information into reliable estimates of outcome learning calls for robust machine learning techniques with high flexibility and accuracy. We applied the novel extreme gradient boosting algorithm for multimodal magnetic resonance imaging-based infarct prediction. METHODS: In a retrospective analysis of 195 patients with acute ischemic stroke, fluid-attenuated inversion recovery, diffusion-weighted imaging, and 10 perfusion parameters were derived from acute magnetic resonance imaging scans...
March 14, 2018: Stroke; a Journal of Cerebral Circulation
David Capper, David T W Jones, Martin Sill, Volker Hovestadt, Daniel Schrimpf, Dominik Sturm, Christian Koelsche, Felix Sahm, Lukas Chavez, David E Reuss, Annekathrin Kratz, Annika K Wefers, Kristin Huang, Kristian W Pajtler, Leonille Schweizer, Damian Stichel, Adriana Olar, Nils W Engel, Kerstin Lindenberg, Patrick N Harter, Anne K Braczynski, Karl H Plate, Hildegard Dohmen, Boyan K Garvalov, Roland Coras, Annett Hölsken, Ekkehard Hewer, Melanie Bewerunge-Hudler, Matthias Schick, Roger Fischer, Rudi Beschorner, Jens Schittenhelm, Ori Staszewski, Khalida Wani, Pascale Varlet, Melanie Pages, Petra Temming, Dietmar Lohmann, Florian Selt, Hendrik Witt, Till Milde, Olaf Witt, Eleonora Aronica, Felice Giangaspero, Elisabeth Rushing, Wolfram Scheurlen, Christoph Geisenberger, Fausto J Rodriguez, Albert Becker, Matthias Preusser, Christine Haberler, Rolf Bjerkvig, Jane Cryan, Michael Farrell, Martina Deckert, Jürgen Hench, Stephan Frank, Jonathan Serrano, Kasthuri Kannan, Aristotelis Tsirigos, Wolfgang Brück, Silvia Hofer, Stefanie Brehmer, Marcel Seiz-Rosenhagen, Daniel Hänggi, Volkmar Hans, Stephanie Rozsnoki, Jordan R Hansford, Patricia Kohlhof, Bjarne W Kristensen, Matt Lechner, Beatriz Lopes, Christian Mawrin, Ralf Ketter, Andreas Kulozik, Ziad Khatib, Frank Heppner, Arend Koch, Anne Jouvet, Catherine Keohane, Helmut Mühleisen, Wolf Mueller, Ute Pohl, Marco Prinz, Axel Benner, Marc Zapatka, Nicholas G Gottardo, Pablo Hernáiz Driever, Christof M Kramm, Hermann L Müller, Stefan Rutkowski, Katja von Hoff, Michael C Frühwald, Astrid Gnekow, Gudrun Fleischhack, Stephan Tippelt, Gabriele Calaminus, Camelia-Maria Monoranu, Arie Perry, Chris Jones, Thomas S Jacques, Bernhard Radlwimmer, Marco Gessi, Torsten Pietsch, Johannes Schramm, Gabriele Schackert, Manfred Westphal, Guido Reifenberger, Pieter Wesseling, Michael Weller, Vincent Peter Collins, Ingmar Blümcke, Martin Bendszus, Jürgen Debus, Annie Huang, Nada Jabado, Paul A Northcott, Werner Paulus, Amar Gajjar, Giles W Robinson, Michael D Taylor, Zane Jaunmuktane, Marina Ryzhova, Michael Platten, Andreas Unterberg, Wolfgang Wick, Matthias A Karajannis, Michel Mittelbronn, Till Acker, Christian Hartmann, Kenneth Aldape, Ulrich Schüller, Rolf Buslei, Peter Lichter, Marcel Kool, Christel Herold-Mende, David W Ellison, Martin Hasselblatt, Matija Snuderl, Sebastian Brandner, Andrey Korshunov, Andreas von Deimling, Stefan M Pfister
Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting...
March 14, 2018: Nature
Carl D Stevens
The sudden, dramatic collapse of the seven-year struggle in Congress to repeal and replace the Affordable Care Act holds important lessons for all would-be reformers, including those advocating fundamental changes in medical education. In this Invited Commentary, the author draws parallels between reform initiatives in health policy and those in medical education, highlighting that, in both settings, stakeholders rarely support "repeal" in the absence of a superior replacement, even when they view the status quo as deeply flawed...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
Golnoosh Ahmadi, Mohsen Shahriari, Mahmood Keyvanara, Shahnaz Kohan
Methods: A qualitative study was used. Midwifery students from three universities in Iran participated. The study used a convenience sample of eighteen students. Data for this study was collected using semi-structured interviews (N=12) and focus groups (N=6). Data were recorded on a digital audio recorder and then transcribed. The qualitative data were analyzed using a content analysis approach. Results: Six broad themes emerged from the analysis: Limited opportunities to experience skills, difficulties with course plan gaps, need for creating a supportive clinical environment, learning drives, confusion between different methods, and stress in the clinical setting...
March 9, 2018: International Journal of Medical Education
Zarrar Shehzad, Gregory McCarthy
Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Early functional MRI studies supported the localizationist perspective that category information was represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately...
March 14, 2018: Journal of Neurophysiology
Kevin A Day, Kristan A Leech, Ryan T Roemmich, Amy J Bastian
Acquiring new movements requires the capacity of the nervous system to remember previously experienced motor patterns. The phenomenon of faster re-learning after initial learning is termed 'savings'. Here we studied how savings of a novel walking pattern develops over several days of practice, and how this process can be accelerated. We introduced participants to a split-belt treadmill adaptation paradigm for 30 minutes for 5 consecutive days. After 5 training days, participants were able to produce near-perfect performance when switching between split and tied-belt environments...
March 14, 2018: Journal of Neurophysiology
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