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PENet-a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging (vol 66, pg 121, 2020)

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NPJ DIGITAL MEDICINE 2020年第1期3卷 61页

作者： Huang, Shih-Cheng Kothari, Tanay Banerjee, Imon Chute, Chris Ball, Robyn L. Borus, Norah Huang, Andrew Patel, Bhavik N. Rajpurkar, Pranav Irvin, Jeremy Dunnmon, Jared Bledsoe, Joseph Shpanskaya, Katie Dhaliwal, Abhay Zamanian, Roham Ng, Andrew Y. Lungren, Matthew P. 1Department of Biomedical Data Science Stanford University Stanford CA USA. 3Department of Computer Science Stanford University Stanford CA USA. 2Center for Artificial Intelligence in Medicine & Imaging Stanford University Stanford CA USA. 5Department of Radiology Stanford University Stanford CA USA. 6Department of Emergency Medicine Intermountain Medical Center Salt Lake Valley UT USA. 7Michigan State University College of Human Medicine East Lansing MI USA. 8Department of Pulmonary Critical Care Medicine Stanford University Stanford CA USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： Cardiovascular diseases Radiography

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ECUTE: Difference is good!

ECUTE: Difference is good!

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IADIS International Conference e-Learning 2012, Part of the IADIS Multi Conference on computer science and Information Systems 2012, MCCSIS 2012

作者： Nazir, Asad Ritter, Christopher Aylett, Ruth Krumhuber, Eva Swiderska, Aleksandra Degens, Nick Endrass, Birgit Hume, Colette Hodgson, John Mascarenhas, Samuel School of Mathematical and Computer Sciences Heriot-Watt University Edinburgh EH14 4AS UK United Kingdom School of Humanities and Social Science Campus Ring 1 28759 Bremen Germany Logistics Decision and Information Sciences Wageningen University 6700 AK Wageningen Netherlands Human Centered Multimedia Augsburg University 86159 Augsburg Germany Department of Computing Engineering and Technology University of Sunderland SR5 0DD United Kingdom Intelligent Agents and Synthetic Characters Group INESC-ID Tagusparque Av. 2744-016 Porto Salvo Portugal

ISBN: (纸本)9789728939717

This paper provides an overview of ongoing research on cultural and emotional learning, thereby utilizing engaging role-play with synthetic characters. The paper explains the underlying learning objectives and provides an overview of how we intend to achieve them. This includes a technical framework integrating affective AI characters and innovative interaction technologies. The framework will be used to realize a virtual learning environment hosting the synthetic characters. Finally a brief description of an evaluation approach for the anticipated learning objectives is given. © 2012 IADIS.

关键词： E-learning

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2021年 12641 LNAI卷 v-vi页

作者： Heintz, Fredrik Milano, Michela O’sullivan, Barry Department of Computer and Information Science Linköping University Linköping Sweden ALMA-AI Research Institute on Human-Centered AI University of Bologna Bologna Italy Department of Computer Science University College Cork Cork Ireland

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Multi-site infant brain segmentation algorithms: The iSeg-2019 challenge

arXiv

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arXiv 2020年

作者： Sun, Yue Gao, Kun Wu, Zhengwang Lei, Zhihao Wei, Ying Ma, Jun Yang, Xiaoping Feng, Xue Zhao, Li Le Phan, Trung Shin, Jitae Zhong, Tao Zhang, Yu Yu, Lequan Li, Caizi Basnet, Ramesh Ahmad, M. Omair Swamy, M.N.S. Ma, Wenao Dou, Qi Bui, Toan Duc Noguera, Camilo Bermudez Landman, Bennett Gotlib, Ian H. Humphreys, Kathryn L. Shultz, Sarah Li, Longchuan Niu, Sijie Lin, Weili Jewells, Valerie Li, Gang Shen, Dinggang Wang, Li The Department of Radiology Biomedical Research Imaging Center University of North Carolina Chapel HillNC27599 United States Northeastern University Shenyang China The Department of Mathematics Nanjing University of Science and Technology Nanjing China The Department of Mathematics Nanjing University China The Department of Biomedical Engineering University of Virginia CharlottesvilleVA United States The Diagnostic Imaging and Radiology Department Children’s National Medical Center WashingtonDC United States The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The School of Biomedical Engineering Southern Medical University Guangzhou510515 China The Chinese University of Hong Kong China Shenzhen Institutes of Advanced Technology China The Department of Electrical and Computer Engineering Concordia University Montreal Canada The School of Informatics Xiamen University China The Department of Computer Science and Engineering The Chinese University of Hong Kong China Electrical Engineering and Computer Science Vanderbilt University NashvilleTN37204 United States The Department of Psychology Stanford University CA94305 United States The Department of Psychology and Human Development Vanderbilt University NashvilleTN37204 United States The Emory University AtlantaGA30322 United States The School of Information Science and Engineering University of Jinan Jinan250022 China The Department of Research and Development Shanghai United Imaging Intelligence Co. Ltd. Shanghai China Department of Brain and Cognitive Engineering Korea University Seoul02841 Korea Republic of

To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance;however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, iSeg-2019 challenge (http://***) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. Training/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participating in iSeg-2019. We review the 8 top-ranked teams by detailing their pipelines/implementations, presenting experimental results and evaluating performance in terms of the whole brain, regions of interest, and gyral landmark curves. We also discuss their limitations and possible future directions for the multi-site issue. We hope that the multi-site dataset in iSeg-2019 and this review article will attract more researchers on the multi-site issue. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance

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A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

arXiv

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arXiv 2017年

作者： Zeng, Xiangrui Leung, Miguel Ricardo Zeev-Ben-Mordehai, Tzviya Xu, Min Computational Biology Department School of Computer Science Carnegie Mellon University Pittsburgh15213 United States Division of Structural Biology Wellcome Trust Centre for Human Genetics University of Oxford OxfordOX3 7BN United Kingdom Cryo-electron Microscopy Bijvoet Center for Biomolecular Research Utrecht University Utrecht Netherlands

Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular tomograms are often complex, making it difficult to automatically isolate different in situ cellular components. In this paper, we propose a convolutional autoencoder-based unsupervised approach to provide a coarse grouping of 3D small subvolumes extracted from tomograms. We demonstrate that the autoencoder can be used for efficient and coarse characterization of features of macromolecular complexes and surfaces, such as membranes. In addition, the autoencoder can be used to detect non-cellular features related to sample preparation and data collection, such as carbon edges from the grid and tomogram boundaries. The autoencoder is also able to detect patterns that may indicate spatial interactions between cellular components. Furthermore, we demonstrate that our autoencoder can be used for weakly supervised semantic segmentation of cellular components, requiring a very small amount of manual annotation. Copyright © 2017, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Research on the Application of Virtual Reality Technology in Landscape Design

Research on the Application of Virtual Reality Technology in...

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International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： R. Senthil Kumar Bhavya K Syed Rizwan Naqvi Murugajothi T S. Joshua Kumaresan Aiman Naqvi Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences(SIMATS) Chennai India Department of Information Science and Engineering NMAM Institute of Technology Nitte(Deemed University) Karnataka India Department of Human Resource and Organizational Behavior Amity Business School Amity University Noida Department of ECE PSNA College of Engineering and Technology Dindigul Tamilnadu India Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences(SIMATS) Chennai India M S Ramaiah Institute of Technology Bangalore India

The purpose of this study is to explore how modern virtual reality technology is applied in India's landscape design. This study provides a brief overview of virtual reality technology and a scientific classification of its main categories. At the same time, the advantages of the currently emerging VR technology are summarised and scientifically analysed and discussed before attempting to apply the technology to landscape design. Research has found that virtual reality can create an immersive environment for users if it is used well in landscape design, bring users a sense of physical and mental enjoyment, and effectively play a more vivid, intuitive, interesting and simple auxiliary role in complex landscape architecture design.

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TAVRNN: TEMPORAL ATTENTION-ENHANCED VARIATIONAL GRAPH RNN CAPTURES NEURAL DYNAMICS AND BEHAVIOR

arXiv

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arXiv 2024年

作者： Khajehnejad, Moein Khajehnejad, Ahmad Habibollahi, Forough Kagan, Brett J. Razi, Adeel Turner Institute for Brain and Mental Health School of Psychological Sciences Monash University Australia Department of Computer Science The University of British Columbia Vancouver Canada Cortical Labs Melbourne Australia Turner Institute for Brain and Mental Health School of Psychological Sciences Monash University Australia Wellcome Centre for Human Neuroimaging University College London United Kingdom

We introduce Temporal Attention-enhanced Variational Graph Recurrent Neural Network (TAVRNN), a novel framework for analyzing the evolving dynamics of neuronal connectivity networks in response to external stimuli and behavioral feedback. TAVRNN captures temporal changes in network structure by modeling sequential snapshots of neuronal activity, enabling the identification of key connectivity patterns. Leveraging temporal attention mechanisms and variational graph techniques, TAVRNN uncovers how connectivity shifts align with behavior over time. We validate TAVRNN on two datasets: in vivo calcium imaging data from freely behaving rats and novel in vitro electrophysiological data from the DishBrain system, where biological neurons control a simulated environment during the game of pong. We show that TAVRNN outperforms previous baseline models in classification, clustering tasks and computational efficiency while accurately linking connectivity changes to performance variations. Crucially, TAVRNN reveals that high game performance in the DishBrain system correlates with the alignment of sensory and motor subregion channels, a relationship not evident in earlier models. This framework represents the first application of dynamic graph representation of electrophysiological (neuronal) data from DishBrain system, providing insights into the reorganization of neuronal networks during learning. TAVRNN’s ability to differentiate between neuronal states associated with successful and unsuccessful learning outcomes, offers significant implications for real-time monitoring and manipulation of biological neuronal systems. © 2024, CC BY.

关键词： Recurrent neural networks

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Analytics in Higher Education: Scoping the Landscape of Research in the Area

Analytics in Higher Education: Scoping the Landscape of Rese...

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International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： Natashaa Kaul Amruta Deshpande Amit Mittal Vishal Jain Symbiosis Center for Management and Human Resource Development Pune India Symbiosis International University Pune India Indira School of Business Studies PGDM Pune India Chitkara Business School Chitkara University Punjab India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida U.P. India

ISBN: (纸本)9781665487351

Understanding the research landscape of any domain is of primary importance at all stages of a concept's evolution. Research in the domain of analytics has increased exponentially in the past decade, analytics is a tool being applied to increase effectiveness and efficiency within all domains. Similarly, there are numerous research studies that have applied analytics to the domain of higher education. Assessing research activity is important for planning future research and identifying the way forward to make meaningful contributions. The objective of this paper is to examine the current research in this domain and to identify emerging areas of research to make meaningful contributions. Bibliometric analysis was applied using Scopus. Documents on analytics and higher education keywords in business, accounting and management and published in journals were considered for the analysis. Vos Viewer was used for bibliometric analysis in the area, to identify emerging research themes and to understand the scope of applying analytics in higher education. The search query found 1635 documents when using the keywords of “analytics” and “higher education”. This was further narrowed down to research in Business Management and Accounting and using Journal articles and conference articles, finally yielding 103 articles. After a primary read to remove articles misplaced in the group the final number of articles include for the bibliometric analysis came down to 98. There has been an increase in publications since 2018 with interest increasing post pandemic in the area. The research categories are Student outcomes and perspective, academician outcomes and perspective, design of learning systems, etc. Based on this, it is recommended that research should focus on theoretical aspects of applying analytics to HEIs, ethical issues in data collection, etc..

关键词： Learning systems Pandemics Education Bibliometrics Data collection Market research Mathematical models

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Dose-response effect of pre-exercise carbohydrates under muscle glycogen unavailability:Insights from McArdle disease

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Journal of Sport and Health science 2024年第3期13卷 398-408页

作者： Pedro L.Valenzuela Alfredo Santalla Lidia B.Alejo Andrea Merlo Asuncion Bustos Laura Castellote-Belles Roser Ferrer-Costa Nicola A.Maffiuletti David Barranco-Gil Tomas Pinos Alejandro Lucia Physical Activity and Health Research Group(“PaHerg”) Research Institute of Hospital“12 de Octubre”(“imas12”)Madrid 28041Spain Department of Systems Biology University of AlcalaMadrid 28871Spain Department of Sport and Computer Science Section of Physical Education and SportsFaculty of SportUniversidad Pablo de OlavideSevilla 41013Spain EVOPRED Research Group Universidad Europea de CanariasTenerife 38300Spain Faculty of Sport Sciences Universidad Europea de MadridMadrid 28670Spain Gait&Motion Analysis Laboratory Sol et Salus HospitalTorre Pedrera di Rimini(RN)47922Italy Department of Clinical Biochemistry Laboratoris ClınicsHospital Universitari Vall d’HebronBarcelona 08035Spain Human Performance Lab Schulthess ClinicZurich 8008Switzerland Biomedical Research Networking Center on Rare Disorders(CIBERER) Barcelona 08035Spain Mitochondrial and Neuromuscular Disorders Unit Vall d’Hebron Institut de RecercaUniversitat Autonoma de BarcelonaBarcelona 08035Spain

Background:This study aimed to determine the effect of different carbohydrate(CHO)doses on exercise capacity in patients with McArdle disease—the paradigm of“exercise intolerance”,characterized by complete muscle glycogen unavailability—and to determine whether higher exogenous glucose levels affect metabolic responses at the McArdle muscle cell(in vitro)***:Patients with McArdle disease(n=8)and healthy controls(n=9)underwent a 12-min submaximal cycling constant-load bout followed by a maximal ramp test 15 min after ingesting a non-caloric *** a randomized,double-blinded,cross-over design,patients repeated the tests after consuming either 75 g or 150 g of CHO(glucose:fructose=2:1).Cardiorespiratory,biochemical,perceptual,and electromyographic(EMG)variables were ***,glucose uptake and lactate appearance were studied in vitro in wild-type and McArdle mouse myotubes cultured with increasing glucose concentrations(0.35,1.00,4.50,and 10.00 g/L).Results:Compared with controls,patients showed the“classical”second-wind phenomenon(after prior disproportionate tachycardia,myalgia,and excess electromyographic activity during submaximal exercise,all p<0.05)and an impaired endurance exercise capacity(-51%ventilatory threshold and55%peak power output,both p<0.001).Regardless of the CHO dose(p<0.05 for both doses compared with the placebo),CHO intake increased blood glucose and lactate levels,decreased fat oxidation rates,and attenuated the second wind in the ***,only the higher dose increased ventilatory threshold(+27%,p=0.010)and peak power output(+18%,p=0.007).In vitro analyses revealed no differences in lactate levels across glucose concentrations in wild-type myotubes,whereas a doseresponse effect was observed in McArdle ***:CHO intake exerts beneficial effects on exercise capacity in McArdle disease,a condition associated with total muscle glycogen *** of these benefits are dose dependent.

关键词： Endurance Glycogen storage disease Glycogenosis Nutrition Supplement

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Correction to: A lightweight signcryption scheme for defense against fragment duplication attack in the 6LoWPAN networks

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Peer-to-Peer Networking and Applications 2018年第1期12卷 227-227页

作者： Nikravan, Mohammad Movaghar, Ali Hosseinzadeh, Mehdi Faculty of Electrical and Computer Engineering Islamic Azad University Science and Research Branch Tehran Iran Department of Computer Engineering Sharif University of Technology Tehran Iran Iran University of Medical Sciences Tehran Iran Computer Science University of Human Development Sulaimaniyah Iraq

The Publisher regrets an incorrect figure was placed in the pdf version of the article.

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