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A survey of explainable artificial intelligence in healthcare: Concepts, applications, and challenges

Informatics in Medicine Unlocked 2024年 51卷

作者： Mienye, Ibomoiye Domor Obaido, George Jere, Nobert Mienye, Ebikella Aruleba, Kehinde Emmanuel, Ikiomoye Douglas Ogbuokiri, Blessing Institute for Intelligent Systems University of Johannesburg Auckland Park Johannesburg 2006 South Africa Center for Human-Compatible Artificial Intelligence (CHAI) Berkeley Institute for Data Science (BIDS) University of California Berkeley 94720 CA United States Department of Computer Science University of Fort Hare Alice Campus Eastern Cape Alice South Africa School of Computing and Mathematical Sciences University of Leicester Leicester LE1 7RH United Kingdom School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Computer Science Brock University Niagara Region St. Catharines L2S 3A1 ON Canada

Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical decisions more transparent, reliable, and ethically compliant. Despite its promise, the healthcare sector faces several challenges, including the need to balance interpretability and accuracy, integrating XAI into clinical workflows, and ensuring adherence to rigorous regulatory standards. This paper provides a comprehensive review of XAI in healthcare, covering techniques, challenges, opportunities, and advancements, thereby enhancing the understanding and practical application of XAI in healthcare. The study also explores responsible AI in healthcare, discussing new perspectives and emerging trends, offering valuable insights for researchers and practitioners. The insights and recommendations presented aim to guide future research and policy-making, fostering the development of transparent, trustworthy, and effective AI-driven solutions. © 2024 The Authors

关键词： AI Bias Ethics Fairness Healthcare Machine learning

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A New Physical Reservoir Using the Complex Dynamics of Electric Fields in Type-Ii Superconductors Containing Pinning centers Interacting with Quantized Flux Lines

SSRN

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SSRN 2024年

作者： Ueda, Tenma Otabe, Edmund Soji Arita, Ken Usami, Yuki Tanaka, Hirofumi Matsuno, Tetsuya Department of Physics and Computer Science Kyushu Institute of Technology 680–4 Kawazu Iizuka Fukuoka820–8502 Japan Department of Human Intelligence Systems Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology 2–4 Hibikino Wakamatsu Kitakyushu808–019 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2–4 Hibikino Wakamatsu Kitakyushu808–019 Japan Department of Creative Engineering National Institute of Technology Ariake College 150 Higashihagio-Machi Omuta Fukuoka836-8585 Japan

Reservoir computing, which takes advantage of physical phenomena with nonlinearities, is attracting a lot of ***, it is expected to focus on superconductivity, a physical phenomenon with nonlinearities between the output electric field and the input current *** to other physical phenomena used in reservoirs, it is considered that with superconductivity, the nonlinearity can easily be adjusted spatially by pin placement to produce dynamics suitable for *** nonlinearity between the electric field generated by the motion of the quantized magnetic flux lines and the input current density was used to perform a reservoir computing *** waveform generation tasks, a NARMA2 task and a nonlinear-memory task were performed, and all tasks were generally *** was found that the electromagnetic phenomenon in superconductors can be used as a physical reservoir. © 2024, The Authors. All rights reserved.

关键词： Electric lines

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Correction: Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes

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International journal of obesity (2005) 2025年第2期49卷 364-365页

作者： Arthur Leroy Varsha Gupta Mya Thway Tint Delicia Shu Qin Ooi Fabian Yap Ngee Lek Keith M Godfrey Yap Seng Chong Yung Seng Lee Johan G Eriksson Mauricio A Álvarez Navin Michael Dennis Wang Department of Computer Science The University of Manchester Manchester UK. Institute for Human Development and Potential Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. Bioinformatics Institute Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. Department of Paediatrics Yong Loo Lin School of Medicine National University of Singapore Singapore Republic of Singapore. Department of Paediatrics KK Women's and Children's Hospital Singapore Republic of Singapore. Duke-NUS Medical School Singapore Republic of Singapore. MRC Lifecourse Epidemiology Centre and NIHR Southampton Biomedical Research Centre University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK. Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Republic of Singapore. Division of Paediatric Endocrinology Department of Paediatrics Khoo Teck Puat-National University Children's Medical Institute National University Hospital National University Health System Singapore Republic of Singapore. Department of General Practice and Primary Health Care University of Helsinki Helsinki Finland. Folkhälsan Research Center Helsinki Finland. Department of Computer Science University of Sheffield Sheffield UK. Institute for Human Development and Potential Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. dennis_wang@sics.a-star.edu.sg. Bioinformatics Institute Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. dennis_wang@sics.a-star.edu.sg. Department of Computer Science University of Sheffield Sheffield UK. dennis_wang@sics.a-star.edu.sg. National Heart and Lung Institute Imperial College London London UK. dennis_wang@sics.a-star.edu.sg.

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Investigating the interrelationships between the barriers of green computing adoption: TISM-MICMAC-DEMATEL method

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Quality and Quantity 2024年第1期59卷 507-570页

作者： Dalvi-Esfahani, Mohammad Nilashi, Mehrbakhsh Abumalloh, Rabab Ali Thurasamy, Ramayah Ahmad, Muhammad Shakil Blockchain Fintech and Cryptocurrency Research Group University of Southampton Malaysia Johor Iskandar Puteri 79100 Malaysia UCSI Graduate Business School UCSI University No. 1 Jalan Menara Gading UCSI Heights Cheras Kuala Lumpur 56000 Malaysia Department of Computer Science and Engineering Qatar University Doha 2713 Qatar School of Management Universiti Sains Malaysia Minden Penang 11800 Malaysia Department of Information Technology and Management Daffodil International University Birulia Bangladesh Department of Management Sunway Business School (SBS) Selangor Petaling Jaya 47500 Malaysia University Center for Research & amp Development (UCRD) Chandigarh University Punjab Ludhiana 140413 India Faculty of Economics and Business Universitas Indonesia (UI) West Java Depok City 16424 Indonesia Management Information Systems Department School of Business The University of Jordan (UJ) Amman 11942 Jordan TUIBS Leadership Management & amp Human Resources Teesside University Middlesbrough United Kingdom Faculty of Business Sohar University Sohar P.C 311 Oman

While a considerable body of research addresses firms’ endeavors toward environmental sustainability, the prominence of green computing has been somewhat eclipsed by impediments hindering its swift integration and development. To address this gap, this study conducted a comprehensive analysis, identifying twelve distinct barriers categorized into adoption costs, technological challenges, and internal obstacles. Through consultation with fifteen field experts, the study employed Interpretive Structural Modeling (ISM) and Matrice d’Impacts Croises Multipication Applique´ an Classment (MICMAC) methodologies to scrutinize the influences among these barriers. The findings illuminated that firm size and legal constraints emerge as pivotal and autonomous factors exerting substantial influence on the adoption. Additionally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was deployed to ascertain the relative importance of these barriers and delineate their causal relationships. Notably, the DEMATEL results underscored that, according to experts, adoption cost barriers hold greater significance compared to other dimensions. Transactional risk, technological complexity, and switching cost were identified as pivotal barriers within their respective dimensions. The decision-making framework formulated in this study offers valuable insights for managers and practitioners, providing a nuanced understanding of the interplay between identified barriers and their implications for implementing green computing initiatives. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： Barriers DEMATEL Green computing MICMAC Total interpretive structural modeling

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A virtual reality methodology for cardiopulmonary resuscitation training with and without a physical mannequin

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Journal of Biomedical Informatics 2020年 111卷 103590页

作者： Buttussi, Fabio Chittaro, Luca Valent, Francesca Human-Computer Interaction Lab Department of Mathematics Computer Science and Physics University of Udine Udine Italy SOC Istituto di Igiene ed Epidemiologia Clinica Azienda Sanitaria Universitaria Friuli Centrale Udine Italy

Background: Cardiopulmonary resuscitation (CPR) is an emergency procedure that can increase survival after a cardiac arrest. Performing CPR effectively requires both procedural knowledge and manual skills. Traditional CPR training methodology includes lessons led by instructors and supervised practice on mannequins, thus requiring considerable resources. Objective: This paper proposes a new methodology for low-cost CPR training based on virtual reality (VR) with and without the addition of a physical mannequin. Moreover, it describes an experimental evaluation of the methodology that assessed gain in manual skills during training, transfer of procedural knowledge and manual skills in a final assessment, and changes in self-efficacy with three measurements over time (pre-training, post-training, and post-assessment). Methods: We implemented a VR application that supports the proposed methodology, and can thus be used with or without a mannequin. The experimental evaluation involved 30 participants who tried CPR in VR twice, performing two repetitions of 30 chest compressions per trial. Half participants tried the VR application with the mannequin and half without it. Final assessment required all participants to perform CPR on the mannequin without the assistance of VR. To assess self-efficacy, participants filled in a questionnaire at the three times of measurement. Results: Mixed-design ANOVAs showed effects of repetition, effects of group, or interaction between the two variables on manual skills assessed during training. In the final assessment, participants in both groups correctly remembered most of the steps of the procedure. ANOVAs revealed differences between the two groups only in pressure-related skills (better with mannequin) and in the number of wrong steps added to the procedure (better without mannequin). Mixed-design ANOVA showed a self-efficacy increase in both groups after training, which was maintained after final assessment. Conclusions: The propo

关键词： Resuscitation

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Queer in HCI: Strengthening the Community of LGBTQIA+ Researchers and Research

Queer in HCI: Strengthening the Community of LGBTQIA+ Resear...

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2021 CHI Conference on human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021

作者： Devito, Michael Ann Lustig, Caitlin Simpson, Ellen Allison, Kimberley Chuanromanee, Tya Spiel, Katta Ko, Amy Rode, Jennifer Dym, Brianna Muller, Michael Klaus Scheuerman, Morgan Marie Walker, Ashley Brubaker, Jed Ahmed, Alex Department of Information Science University of Colorado United States Human Centered Design and Engineering University of Washington United States School of Information Studies Syracuse University United States Department of Psychology Macquarie University Australia University of Notre Dame United States Human-Computer Interaction Group Tu Wien Austria The Information School University of Washington United States Knowledge Lab University College London United Kingdom Department of Information Science University of Colorado Boulder United States Ai Interactions Ibm Research United States Information Science University of Colorado Boulder United States Pitch Lab Northwestern University United States University of Colorado Boulder United States Carnegie Mellon University United States

ISBN: (纸本)9781450380959

As Queer human-computer interaction (HCI) becomes an established part of the larger field, both in terms of research on and with queer populations and in terms of employing queering theories and methods, the role of queer researchers has become a timely topic of discussion. However, these discussions have largely centered around member-researcher status and positionality when working with queer populations. Based on insights gathered at multiple ACM events over the past two years, we identified two pressing issues: (1) we need to better support queer people doing HCI research not specific to queer populations, and (2) we need to identify how to best support member-researchers in leading Queer HCI while including collaborators beyond the queer community. This Special Interest Group (SIG) aims to directly address these challenges by convening a broad community of queer researchers and allies, working not only on explicitly-queer topics but across a broad range of HCI topics. © 2021 Owner/Author.

关键词： Computation theory

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Sustainability in the Internet of Production: Interdisciplinary Opportunities and Challenges

Sustainability in the Internet of Production: Interdisciplin...

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International Symposium on Technology and Society (ISTAS)

作者： Sebastian Bernhard Sebastian Pütz Calvin Röhl Ralph Baier Philipp Brauner Ester Christou Hannah Dammers Roman Flaig Leon M. Gorißen Jan-Christoph Heilinger Christian Hinke István Koren Dirk Lüttgens Michael Millan Kai Müller Alexander Schollemann Luisa Vervier Thomas Gries Alexander Mertens Saskia K. Nagel Frank T. Piller Günther Schuh Martina Ziefle Verena Nitsch Carmen Leicht-Scholten Gender and Diversity in Engineering RWTH Aachen University Aachen Germany Institute of Industrial Engineering and Ergonomics RWTH Aachen University Aachen Germany Human-Computer Interaction Center RWTH Aachen University Aachen Germany Institute for Technology and Innovation Management RWTH Aachen University Aachen Germany Institut für Textiltechnik RWTH Aachen University Aachen Germany Chair for Laser Technology RWTH Aachen University Aachen Germany Human Technology Center/Applied Ethics RWTH Aachen University Aachen Germany Chair of Process and Data Science RWTH Aachen University Aachen Germany Laboratory for Machine Tools and Production Engineering RWTH Aachen University Aachen Germany

The vision of the Internet of Production (loP) is focused on optimizing manufacturing processes, with the help of Industry 4.0 technologies (14Ts). However, considering global megatrends such as climate change and the need to achieve the Sustainable Development Goals (SDGs), it is a growing imperative for the manufacturing industry to become more sustainable. This opens the door to transforming the IoP into an Internet of Sustainable Production (loSP). Accordingly, this paper proposes a novel four-step loSP-framework that establishes an Information System (IS) allowing researchers and practitioners to acknowledge and adapt to the interconnected nature of sustainability. Further, to test its applicability, an inter- and cross-disciplinary perspective is adopted to illustrate case-related challenges, opportunities, and pathways - revealed by the proposed framework - in the example of a digital economy for sustainability data, strategic design of global production networks, human-robot collaboration, digital photonic production, and the textile industry. Together, the framework demonstrates the usefulness of generating holistic information on the interconnected nature of sustainability derived from process-specific and contextualized data, while simultaneously assessing the framework's utilization for sustainability, as well as the sustainability of its use.

关键词：

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Building human Values into Recommender Systems: An Interdisciplinary Synthesis

arXiv

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arXiv 2022年

作者： Stray, Jonathan Halevy, Alon Assar, Parisa Hadfield-Menell, Dylan Boutilier, Craig Ashar, Amar Beattie, Lex Ekstrand, Michael Leibowicz, Claire Sehat, Connie Moon Johansen, Sara Kerlin, Lianne Vickrey, David Singh, Spandana Vrijenhoek, Sanne Zhang, Amy Andrus, McKane Helberger, Natali Proutskova, Polina Mitra, Tanushree Vasan, Nina Center for Human-Compatible Artificial Intelligence UC Berkeley United States Meta AI United States Department of Electrical Engineering and Computer Science MIT United States Google Research United States Spotify Inc. Computer Science Department Boise State University United States Partnership on AI Hacks/Hackers Brainstorm The Stanford Lab for Mental Health Innovation Department of Psychiatry and Behavioral Sciences Stanford University United States BBC United Kingdom Meta United States New America's Open Technology Institute United States Faculty of Law Information Law University of Amsterdam Netherlands Allen School of Computer Science & Engineering University of Washington United States Institute for Information Law University of Amsterdam Netherlands Information and Computer Science University of Washington United States

Recommender systems are the algorithms which select, filter, and personalize content across many of the world's largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ensure that recommender systems enact the values of the individuals and societies that they serve. Addressing this question in a principled fashion requires technical knowledge of recommender design and operation, and also critically depends on insights from diverse fields including social science, ethics, economics, psychology, policy and law. This paper is a multidisciplinary effort to synthesize theory and practice from different perspectives, with the goal of providing a shared language, articulating current design approaches, and identifying open problems. It is not a comprehensive survey of this large space, but a set of highlights identified by our diverse author cohort. We collect a set of values that seem most relevant to recommender systems operating across different domains, then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches. Important open problems include multi-stakeholder processes for defining values and resolving trade-offs, better values-driven measurements, recommender controls that people use, non-behavioral algorithmic feedback, optimization for long-term outcomes, causal inference of recommender effects, academic-industry research collaborations, and interdisciplinary policy-making. Copyright © 2022, The Authors. All rights reserved.

关键词： Recommender systems

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A Simulation Study of Transcranial Magnetoacoustic Stimulation of the Basal Ganglia Thalamic Neural Network to Improve Parkinson's Disease Status

SSRN

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SSRN 2023年

作者： Zhang, Yanqiu Zhang, Hao Xu, Tianya Liu, Jiahe Mu, Jiayang Chen, Rongjie Yang, Jiumin Wang, Peiguo Jian, Xiqi School of Biomedical Engineering and Technology Tianjin Medical University Tianjin300070 China Academy of Medical Engineering and Translational Medicine Tianjin International Joint Research Centre for Neural Engineering Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin University Tianjin300072 China Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin300392 China Neurology Department Tianjin Huanhu Hospital Tianjin300350 China Department of Oncology Radiotherapy Cancer Institute Hospital of Tianjin Medical University Tianjin300202 China

Background: Parkinson's disease (PD) is a common neurodegenerative disease. Transcranial magnetoacoustic stimulation (TMAS) is a new therapy that combines a transcranial focused acoustic pressure field with a magnetic field to excite or inhibit neurons in targeted area, which suppresses the abnormally elevated beta band amplitude in PD states, with high spatial resolution and non-invasively. Objective: To study the effective stimulation parameters of TMAS mononuclear and multinuclear stimulation for the treatment of PD with reduced beta band energy, improved abnormal synchronization, and no thermal damage. Methods: The TMAS model is constructed based on the volunteer's computed tomography, 128 arrays of phase-controlled transducers, and permanent magnets. A basal ganglia-thalamic (BG-Th) neural network model of the PD state was constructed on the basis of the Izhikevich model and the acoustic model. An ultrasound stimulation neuron model is constructed based on the Hodgkin-Huxley model. Numerical simulations of transcranial focused acoustic pressure field, temperature field and induced electric field at single and dual targets were performed using the locations of STN, GPi, and GPe in the human brain as the main stimulation target areas. And the acoustic and electric parameters at the focus were extracted to stimulate mononuclear and multinuclear in the BG-Th neural network. Results: When the stimulating effect of ultrasound is ignored, TMAS-STN suppresses the beta band amplitude of each nucleus, whereas TMAS-GPi affects only some nuclei. TMAS-STN&GPi can reduce the beta band amplitude. TMAS-STN&GPi&GPe is more effective. When considering the stimulatory effect of ultrasound, the stimulatory effect of lower sound pressures is negligible, but higher sound pressures may promote or inhibit the stimulatory effect of induced currents. Conclusions: TMAS stimulation of multinuclear with appropriate ultrasound intensity is effective in PD and may be clinically useful. © 202

关键词： Ultrasonics

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AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Shahzad, Sahibzada Adil Hashmi, Ammarah Peng, Yan-Tsung Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Multimodal manipulations (also known as audiovisual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of false propaganda and fake news, timely detection is crucial. The damage to either modality (i.e., visual or audio) can only be discovered through multi-modal models that can exploit both pieces of information simultaneously. Previous methods mainly adopt uni-modal video forensics and use supervised pre-training for forgery detection. This study proposes a new method based on a multi-modal self-supervised-learning (SSL) feature extractor to exploit inconsistency between audio and visual modalities for multi-modal video forgery detection. We use the transformer-based SSL pre-trained Audio-Visual HuBERT (AV-HuBERT) model as a visual and acoustic feature extractor and a multi-scale temporal convolutional neural network to capture the temporal correlation between the audio and visual modalities. Since AV-HuBERT only extracts visual features from the lip region, we also adopt another transformer-based video model to exploit facial features and capture spatial and temporal artifacts caused during the deepfake generation process. Experimental results show that our model outperforms all existing models and achieves new state-of-the-art performance on the FakeAVCeleb and DeepfakeTIMIT datasets. © 2023, CC BY.

关键词： Audio acoustics

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