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An Ontology Model for Medical Tourism Supply Chain Knowledge Representation
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Science and Information Organization
, 2022 , Article)
This study developed an application ontology related to the medical tourism supply chain domain (MTSC). The motivation for developing an ontology is that current MTSC studies use a descriptive approach to provide knowledge, ...
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
To assist policymakers in making adequate decisions to stop the spread of the COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance. This paper presents a deep learning approach to ...
DL-CRC: Deep learning-based chest radiograph classification for covid-19 detection: A novel approach
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
With the exponentially growing COVID-19 (coronavirus disease 2019) pandemic, clinicians continue to seek accurate and rapid diagnosis methods in addition to virus and antibody testing modalities. Because radiographs such ...
Blockchain for decentralized multi-drone to combat COVID-19 and future pandemics: Framework and proposed solutions
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John Wiley and Sons Inc
, 2021 , Article)
Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic ...
FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
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Elsevier
, 2022 , Article)
Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ...
Pore-scale simulation of fine particles migration in porous media using coupled CFD-DEM
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Elsevier
, 2022 , Article)
Transport of fine particles in porous media has attracted a considerable interest over the past several decades given its importance to many industrial and natural processes. In order to control fine particles transport ...
Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges
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Taylor & Francis
, 2022 , Article)
Cyberattacks are becoming more and more intense in the banking industry (Ryzhkova et al. 2020). Banking industry is trying to adopt artificial intelligence to create cyber defence system so that the unauthorized access and ...
Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors
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Elsevier
, 2022 , Article)
Retinal images acquired using fundus cameras are often visually blurred due to imperfect imaging conditions, refractive medium turbidity, and motion blur. In addition, ocular diseases such as the presence of cataracts also ...
Robust Enhancement of Intrusion Detection Systems Using Deep Reinforcement Learning and Stochastic Game
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
The incorporation of advanced networking technologies makes modern systems vulnerable to cyber-attacks that can result in a number of harmful outcomes. Due to the increase of security incidents and massive activities on ...
An active learning method for diabetic retinopathy classification with uncertainty quantification
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Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
In recent years, deep learning (DL) techniques have provided state-of-the-art performance in medical imaging. However, good quality (annotated) medical data is in general hard to find due to the usually high cost of medical ...