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Ray: A Distributed Framework for Emerging AI Applications
[article]
2018
arXiv
pre-print
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To meet the performance requirements, Ray employs a distributed scheduler and a distributed and fault-tolerant store to manage the system's control state. ...
In this paper, we consider these requirements and present Ray---a distributed system to address them. ...
We are grateful to our anonymous reviewers and our shepherd, Miguel Castro, for thoughtful feedback, which helped improve the quality of this paper. ...
arXiv:1712.05889v2
fatcat:odyn47sxe5fstcknououtih4sm
Seismic ray-impedance inversion
[chapter]
2016
Seismic Inversion
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An analysis of P-P and P-S wave data under the framework of ray impedance is conducted through a real multicomponent dataset, which can reduce the uncertainty in lithology identification. ...
With the estimated wavelets ready, a Cauchy inversion method is used to invert for seismic reflectivity sequences, aiming at recovering seismic reflectivity sequences for blocky impedance inversion. ...
The EI provides a consistent and absolute framework to calibrate and invert nonzero-offset seismic data just as AI does for zerooffset data. ...
doi:10.1002/9781119258032.ch10
fatcat:dozbwj4e2re23lzffv3xrjeff4
Digital technology in management of Covid-19: A new ray to healthcare
2020
International Journal of Research in Pharmaceutical Sciences
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The term AI refers to a variety of instruments utilized for distinguishing designs in the information. ...
Rather than conventional techniques for design recognizable proof, AI instruments depend on Artificial Intelligence consciousness to delineate patterns from a lot of information, would self be able to ...
Con lict of Interest The authors declare that they have no con lict of interest for this study.
Funding Support The authors declare that they have no funding support for this study. ...
doi:10.26452/ijrps.v11ispl1.3684
fatcat:zx6or6kadzbkbaqwuey2pf4d74
Experiments of Federated Learning for COVID-19 Chest X-ray Images
[article]
2020
arXiv
pre-print
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AI plays an important role in COVID-19 identification. Computer vision and deep learning techniques can assist in determining COVID-19 infection with Chest X-ray Images. ...
And we also compare performances of four popular models (MobileNet, ResNet18, MoblieNet, and COVID-Net) with the federated learning framework and without the framework. ...
A key step in judging and treating COVID-19 is the effective screening of infected patients. One of the key screening methods is the use of chest X-rays for radiology. ...
arXiv:2007.05592v1
fatcat:tvme47nw6rbxraeyy3uv46n6pa
Doctors+
2020
E3S Web of Conferences
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It expects to give minimal effort solid mechanization of existing frameworks. The framework gives incredible assurance of information at each degree of a client framework collaboration. ...
AI-Powered Chatbots for patients etc. 3006
https://doi.org/10.1051/e3sconf/202017003006
3.11 Dashboard for pharmacists
Fig.14. ...
In this way, remembering crafted by the manual framework as the premise of our undertaking, we have built up a computerized variant of the manual framework assigned as "Doctors +". ...
doi:10.1051/e3sconf/202017003006
fatcat:cvt2nyxnj5hajmm4rr7rhussva
Designing Futuristic Telemedicine Using Artificial Intelligence and Robotics in the COVID-19 Era
2020
Frontiers in Public Health
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framework to accelerate the rapid deployment of telemedicine and improve access to quality and cost-effective healthcare. ...
This paper discusses various artificial intelligence and robotics-assisted telemedicine or telehealth applications during COVID-19 and presents an alternative artificial intelligence assisted telemedicine ...
The current paper is a call for the integration of AI, robotics, and telemedicine with an organizational framework powered by AI to accelerate healthcare delivery and improve access to healthcare in the ...
doi:10.3389/fpubh.2020.556789
pmid:33224912
pmcid:PMC7667043
fatcat:reucmg5xfre7lb3ji3wrkwlsja
Beyond the promise: implementing ethical AI
2020
AI and Ethics
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To mitigate these risks, a growing number of organisations are working on ethical AI principles and frameworks. ...
Artificial Intelligence (AI) applications can and do have unintended negative consequences for businesses if not implemented with care. ...
Dissent is an important element of a robust governance framework. ...
doi:10.1007/s43681-020-00011-6
fatcat:yh2amlgmcrcxlfeta7yzcwkh3a
Ray Traced Shadows: Maintaining Real-Time Frame Rates
[chapter]
2019
Ray Tracing Gems
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We present a practical method for ray traced shadows in real-time applications. ...
With recent advances of graphics hardware, it is now possible to use ray tracing in real-time applications, making ray traced shadows a viable alternative to rasterization. ...
ACKNOWLEDgEMENTS We thank Tomas Akenine-Möller for his feedback and help with the performance measurements, Nir Benty for assistance with the Falcor framework, and David Sedlacek for providing the environment ...
doi:10.1007/978-1-4842-4427-2_13
fatcat:bmr6idd725a6piqgxx6jt3fnqa
Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation
2020
European Radiology
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Methods We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital-specific CXR generation rates and reporting rates and pathology distribution ...
Conclusion Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO. ...
We develop a realistic simulation framework and evaluate whether AI can reduce RTAT for critical findings by using smart worklist prioritization instead of the standard FIFO sorting. ...
doi:10.1007/s00330-020-07480-7
pmid:33219850
fatcat:2cxeayyxeran5cv2kha2x7dka4
COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays
[article]
2020
arXiv
pre-print
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In view of this need, we present COVID-MobileXpert: a lightweight deep neural network (DNN) based mobile app that can use chest X-ray (CXR) for COVID-19 case screening and radiological trajectory prediction ...
We design and implement a novel three-player knowledge transfer and distillation (KTD) framework including a pre-trained attending physician (AP) network that extracts CXR imaging features from a large ...
From a more broad perspective, the three-player KTD framework is generally applicable to train other on-device medical imaging classification and segmentation apps for point-of-care screening of other ...
arXiv:2004.03042v3
fatcat:cimufv6mqragpm35m55ncwz5vm
Requirement analysis for an artificial intelligence model for the diagnosis of the COVID-19 from chest X-ray data
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2110.12464v1 fatcat:6uuom52ilzftffeb4eu43orpx4
COVID-19 from chest X-ray data (CXR). ...
In this paper I go through multiple review papers, guidelines, and other relevant material in order to generate more comprehensive requirements for the future papers proposing a AI based diagnosis of the ...
This analysis is based on the framework provided in the reference [18] which provides a list of questions for consideration. ...
arXiv:2110.12464v2
fatcat:ioshf2tvf5eqxnuqwywobhdcdm
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
[article]
2021
arXiv
pre-print
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While contrastive learning has demonstrated promising results on natural image classification tasks, its application to medical imaging tasks like chest X-ray interpretation has been limited. ...
of pathologies in chest X-rays. ...
step for successful application on chest X-rays. ...
arXiv:2010.05352v3
fatcat:std5cfpt7zec7f765qxuvlekhy
SODA: Detecting Covid-19 in Chest X-rays with Semi-supervised Open Set Domain Adaptation
[article]
2020
arXiv
pre-print
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SODA is able to align the data distributions across different domains in a general domain space and also in a common subspace of source and target data. ...
Most of these works first train a Convolutional Neural Network (CNN) on an existing large-scale chest x-ray image dataset and then fine-tune it with a COVID-19 dataset at a much smaller scale. ...
Annotated datasets are required for training AI-based methods, and a small chest x-ray dataset with COVID-19 is collected recently: COVID-ChestXray [6] . ...
arXiv:2005.11003v2
fatcat:2kfhloiwxjgprgejqrmcws4lx4
COVIDScreen: explainable deep learning framework for differential diagnosis of COVID-19 using chest X-rays
2021
Neural computing & applications (Print)
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COVID-19 has emerged as a global crisis with unprecedented socio-economic challenges, jeopardizing our lives and livelihoods for years to come. ...
In this article, we propose a novel deep learning-based solution using chest X-rays which can help in rapid triaging of COVID-19 patients. ...
Arun for his valuable suggestions during the course of this work.
Compliance with ethical standards ...
doi:10.1007/s00521-020-05636-6
pmid:33437132
pmcid:PMC7791540
fatcat:6fxeubkozvft5oeg7egly42il4
The Road to Big Data Standardisation
[chapter]
2021
The Elements of Big Data Value
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Starting with an overview of standardisation as a means for achieving interoperability, the chapter moves on to identify the European Standards Development Organizations that contribute to the European ...
Commission's plan for the Digital Single Market. ...
Acknowledgements This chapter is supported in part by the ADAPT SFI Centre for Digital Content Technology, which is funded under the SFI Research Centres Programme (Grant 13/RC/ 2106) and is co-funded ...
doi:10.1007/978-3-030-68176-0_14
fatcat:kx4oudr2lndmdjkamu5u33quvi
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