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Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography

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arXiv 2024年

作者： Toivanen, J. Kolehmainen, V. Paldanius, A. Hänninen, A. Hauptmann, A. Hamilton, S.J. Department of Technical Physics University of Eastern Finland KuopioFI-70210 Finland Faculty of Medicine and Health Technology Tampere University Tampere Finland Department of Mathematical and Statistical Sciences Marquette University MilwaukeeWI53233 United States Research Unit of Mathematical Sciences University of Oulu Oulu Finland Department of Computer Science University College London London United Kingdom

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to computationally expensive nonlinear model-based methods. Methods: A post-processing approach with graph convolutional networks is employed. Utilizing the flexibility of the graph setting, a graph U-net is trained on linear difference reconstructions from 2D simulated stroke data and applied to fully 3D images from realistic simulated and experimental data. An additional network, trained on 3D vs. 2D images, is also considered for comparison. Results: Post-processing the linear difference reconstructions through the graph U-net significantly improved the image quality, resulting in images comparable to, or better than, the time-intensive nonlinear reconstruction method (a few minutes vs. several hours). Conclusion: Pairing a fast reconstruction method, such as linear difference imaging, with post-processing through a graph U-net provided significant improvements, at a negligible computational cost. Training in the graph framework vs classic pixel-based setting (CNN) allowed the ability to train on 2D cross-sectional images and process 3D volumes providing a nearly 50x savings in data simulation costs with no noticeable loss in quality. Significance: The proposed approach of post-processing a linear difference reconstruction with the graph U-net could be a feasible approach for on-line monitoring of hemorrhagic stroke. Copyright © 2024, The Authors. All rights reserved.

关键词： Image quality

HealthyBlockchain for Global Patients

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computers, Materials & Continua 2021年第8期68卷 2431-2449页

作者： Shada A.Alsalamah Hessah A.Alsalamah Thamer Nouh Sara A.Alsalamah College of Computer and Information Sciences King Saud UniversityRiyadh11451Saudi Arabia Digital Health and Innovation Science DivisionWorld Health OrganizationGenevaCH-1211Switzerland MIT Department of Mechanical Engineering Massachusetts Institute of Technology(MIT)Cambridge02139MAUSA College of Engineering and Architecture Al Yamamah UniversityRiyadh11451Saudi Arabia Trauma and Acute Care Surgery Unit College of MedicineKing Saud UniversityRiyadh11451Saudi Arabia College of Computer and Information Sciences Al Imam Mohammad Ibn Saud Islamic UniversityRiyadh13318Saudi Arabia

An emerging healthcare delivery model is enabling a new era of clinical care based on well-informed decision-making *** healthcare information systems(HISs)fall short of adopting this model due to a conflict between information security needed to implement the new model and those already enforced locally to support traditional care ***,in recent times,the healthcare sector has shown a substantial interest in the potential of using blockchain technology for providing quality care to *** blockchain solution proposed so far has fully addressed emerging cross-organization information-sharing needs in *** this paper,we aim to study the use of blockchain in equipping struggling HISs to cope with the demands of the new healthcare delivery model,by proposing HealthyBlockchain as a granular patient-centered ledger that digitally tracks a patient’s medical transactions all along the treatment pathway to support the care *** patient-centered ledger is a neutral tamper-proof trail timestamp block sequence that governs distributed patient information across the decentralized discrete *** connects patients,clinicians,and healthcare providers to facilitate a transparent,trustworthy,and secure supporting platform.

关键词： Blockchain eHealth electronic health record global patient healthcare information system information security legacy system patient-centered care privacy smart contract trust

An Exploration Study on Developing Blockchain Systems – the Practitioners’ Perspective

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arXiv 2024年

作者： Aljedaani, Bakheet Ahmad, Aakash Fahmideh, Mahdi Khan, Arif Ali Shen, Jun Computer Science Department Aljumum University College Umm Alqura University Makkah Saudi Arabia School of Computing and Communications Lancaster University Leipzig Germany School of Business University of Southern Queensland QLD Australia M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland School of Computing and Information Technology University of Wollongong Wollongong Australia

Context: Blockchain-based software (BBS) exploits the concepts and technologies popularized by cryptocurrencies like Bitcoin, offering decentralized transaction ledgers with immutable content for security-critical and transaction-critical systems. Recent research has explored the strategic benefits and technical limitations of BBS in various fields, including cybersecurity, healthcare, education, and financial technologies. Despite growing interest from academia and industry, there is a lack of empirical evidence, leading to an incomplete understanding of the processes, methods, and techniques necessary for systematic BBS development. Objectives: Existing research lacks a consolidated view, particularly empirically-driven guidelines based on published evidence and development practices. This study aims to address the gap by consolidating empirical evidence and development practices to derive or leverage existing processes, patterns, and models for designing, implementing, and validating BBS systems. Method: Tied to this knowledge gap, we conducted a two-phase research project. First, a systematic literature review of 58 studies was performed to identify a development process comprising 23 tasks for BBS systems. Second, a survey of 102 blockchain practitioners from 35 countries across six continents was conducted to validate the BBS system development process. Results: Our results revealed a statistically significant difference (p-value © 2024, CC BY-NC-SA.

关键词： Decentralized finance

Connecting Quantum Cities: Simulation of a Satellite-Based Quantum Network

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arXiv 2023年

作者： Yehia, Raja Schiavon, Matteo Acosta, Valentina Marulanda Coopmans, Tim Kerenidis, Iordanis Elkouss, David Diamanti, Eleni Sorbonne Université CNRS LIP6 ParisF-75005 France Université de Paris CNRS IRIF ParisF-75013 France ICFO - Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Spain DOTA ONERA Université Paris Saclay ChâtillonF-92322 France QuTech Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Leiden Institute of Advanced Computer Science Leiden University Niels Bohrweg 1 CA Leiden2333 Netherlands Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan

We present and analyse an architecture for a European-scale quantum network using satellite links to connect Quantum Cities, which are metropolitan quantum networks with minimal hardware requirements for the end users. Using NetSquid, a quantum network simulation tool based on discrete events, we assess and benchmark the performance of such a network linking distant locations in Europe in terms of quantum key distribution rates, considering realistic parameters for currently available or near-term technology. Our results highlight the key parameters and the limits of current satellite quantum communication links and can be used to assist the design of future missions. We also discuss the possibility of using high-altitude balloons as an alternative to satellites. © 2023, CC BY-NC-SA.

关键词： Satellites

Classical Machine Learning: Seventy Years of Algorithmic Learning Evolution

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arXiv 2024年

作者： Ezugwu, Absalom E. Ho, Yuh-Shan Egwuche, Ojonukpe S. Ekundayo, Olufisayo S. Van Der Merwe, Annette Saha, Apu K. Pal, Jayanta Unit for Data Science and Computing North-West University 11 Hoffman Street Potchefstroom2520 South Africa Trend Research Centre Asia University No. 500 Lioufeng Road Taichung41354 Taiwan School of Computer Science and Information Systems North-West University 11 Hoffman Street Potchefstroom2520 South Africa Department of Mathematics National Institute of Technology Agartala Tripura Agartala799046 India Department of IT Tripura University Suryamaninagar Tripura 799022 India

Machine learning (ML) has transformed numerous fields, but understanding its foundational research is crucial for its continued progress. This paper presents an overview of the major classical ML algorithms and examines the state-of-the-art publications, spanning twelve decades, through an extensive bibliometric analysis study. We analyzed a dataset of highly cited papers from prominent ML conferences and journals, employing techniques such as citation and keyword analyses to uncover key insights. The study further identifies the most influential papers and authors, reveals the evolving collaborative networks within the ML community, and pinpoints prevailing research themes and emerging areas of focus. Additionally, we examine the geographic distribution of highly cited publications, highlighting the leading countries in ML research. This study provides a comprehensive overview of the evolution of traditional learning algorithms, and their impacts, and discusses challenges and opportunities for future development, with a particular focus on the Global South. The findings from this paper offer valuable insights for both ML experts and the broader research community, enhancing understanding of the field's trajectory and its significant influence on recent advances in learning algorithms. © 2024, CC BY.

关键词： Adversarial machine learning

Utility of convolutional neural network-based algorithm in medical images for liver fibrosis assessment

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Chinese Medical Journal 2021年第18期134卷 2255-2257页

作者： Wei Wei Xu Yang Clinical Epidemiology and EBM Unit Beijing Friendship HospitalCapital Medical UniversityBeijing 100050China National Clinical Research Center for Digestive Diseases Beijing 100050China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China

To the Editor:Liver fibrosis is the critical stage leading to hepatic dysfunction and might be important in the progress to portal hypertension,biliary cirrhosis,and hepatocellular ***,the accurate assessment of liver fibrosis remains a clinical concern for *** recent researches,liver biopsy has been considered the golden standard for the diagnostic and assessment of liver fibrosis for many ***,due to its invasive practice,sampling variability,and inter-and intra-assessor variability of pathological interpretations,liver biopsy is not well received in the patients and clinical physicians in many *** a result,multiple non-invasive detections of hepatic fibrosis assessment have been developed as an alternative strategy for liver biopsy as they could offer a convenient operation and acceptable diagnostic accuracy through medical imaging *** detection of hepatic fibrosis through clinical imaging could reduce liver failure and prevent its *** interpretation and analysis of medical imaging information are usually performed by clinical *** from the rapid development of computer-aided diagnosis,especially the improved algorithm of deep learning in artificial intelligence,physicians could extract more accurate assessment for clinical decisions for diagnosis and treatment.[1]

关键词： diagnosis neural algorithm

Proceedings of 3rd International Conference on computer Vision and Image Processing 1

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丛书名： Advances in Intelligent Systems and Computing

2020年

作者： Bidyut B. Chaudhuri Masaki Nakagawa Pritee Khanna Sanjeev Kumar

Promoting Criticality with Design Futuring with Young Children 24

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Promoting Criticality with Design Futuring with Young Childr...

Proceedings of the 13th Nordic Conference on Human-computer Interaction

作者： Sumita Sharma Noura Howell Leena Ventä-Olkkonen Netta Iivari Grace Eden Heidi Hartikainen Marianne Kinnula Eva Durall Michael Nitsche Jussi Okkonen Supratim Pait Elisa Rubegni Wouter Sluis-Thiescheffer Lonneke van der Velden Uttishta Sreerama Varanasi INTERACT Research Unit University of Oulu Finland Digital Media Georgia Institute of Technology United States University of Tartu Estonia INTERACT University of Oulu Finland Digital Media/ School of Literature Media and Communication Georgia Institute of Technology United States Tampere University Finland School of Computing and Communication Lancaster University United Kingdom Media Design HAN University of Applied Sciences Netherlands University of Amsterdam Netherlands Department of Computer Science Aalto University Finland

ISBN: (纸本)9798400709661

As children's everyday interaction with emerging technologies increases, they need to develop criticality to navigate ethical impacts of technology and when imagining futures with technology. We explore how design futuring can facilitate children's criticality through four different workshops with children from India, Finland, and the USA. Participants imagined futures with technologies while critically considering ethical impacts. In the findings, themes related to empowerment and ethics emerged in children's imagined futures. We discuss promoting criticality and empowerment with children's imagined futures, and how these futures can respond to diverse, local issues based on their lived experiences. Our work diversifies design research by highlighting local futures, and the criticality of those imagined futures, from children across the world.

关键词： Child-centered AI

Structure Function Based Transform Features for Behavior-Oriented Social Media Image Classification 5th

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Structure Function Based Transform Features for Behavior-Ori...

5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Krishnani, Divya Shivakumara, Palaiahnakote Lu, Tong Pal, Umapada Ramachandra, Raghavendra International Institute of Information Technology Naya Raipur Naya RaipurChhattisgarh India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia National Key Lab for Novel Software Technology Nanjing University Nanjing China Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9783030414030

Social media has become an essential part of people to reflect their day to day activities including emotions, feelings, threatening and so on. This paper presents a new method for the automatic classification of behavior-oriented images like Bullying, Threatening, Neuroticism-Depression, Neuroticism-Sarcastic, Psychopath and Extraversion of a person from social media images. The proposed method first finds facial key points for extracting features based on a face detection algorithm. Then the proposed method labels face regions as foreground and other than face region as background to define context between foreground and background information. To extract context, the proposed method explores Structural Function based Transform (SFBT) features, which study variations on pixel values. To increase discriminating power of the context features, the proposed method performs clustering to integrate the strength of the features. The extracted features are then fed to Support Vector Machines (SVM) for classification. Experimental results on a dataset of six classes show that the proposed method outperforms the existing methods in terms of confusion matrix and classification rate. © Springer Nature Switzerland AG 2020.

关键词： Classification (of information)