AIMC Topic: COVID-19
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A multistage multimodal deep learning model for disease severity assessment and early warnings of high-risk patients of COVID-19.
Frontiers in public health
Nov 22, 2022
The outbreak of coronavirus disease 2019 (COVID-19) has caused massive infections and large death tolls worldwide. Despite many studies on the clinical characteristics and the treatment plans of COVID-19, they rarely conduct in-depth prognostic resea...
An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets.
Mathematical biosciences and engineering : MBE
Nov 21, 2022
The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over the world. As of December 31, 2021, more than 2, 86, 901, 222 people have been infected with COVID-1...
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets.
Sensors (Basel, Switzerland)
Nov 21, 2022
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possib...
A PROMETHEE based outranking approach for the construction of Fangcang shelter hospital using spherical fuzzy sets.
Artificial intelligence in medicine
Nov 19, 2022
This study mainly aims to develop two effective and practical multi-criteria group decision-making approaches by taking advantage of the ground-breaking theory of PROMETHEE family of outranking methods. The presented variants of Preference Ranking Or...
Identification of hospitalized mortality of patients with COVID-19 by machine learning models based on blood inflammatory cytokines.
Frontiers in public health
Nov 17, 2022
Coronavirus disease 2019 (COVID-19) spread worldwide and presented a significant threat to people's health. Inappropriate disease assessment and treatment strategies bring a heavy burden on healthcare systems. Our study aimed to construct predictive ...
Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.
PloS one
Nov 16, 2022
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can provide useful information to clinical staff for facilitating a diagnosi...
Generative adversarial network based data augmentation for CNN based detection of Covid-19.
Scientific reports
Nov 10, 2022
Covid-19 has been a global concern since 2019, crippling the world economy and health. Biological diagnostic tools have since been developed to identify the virus from bodily fluids and since the virus causes pneumonia, which results in lung inflamma...
MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images.
IEEE journal of biomedical and health informatics
Nov 10, 2022
Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its spread. Slow testing results of reverse transcription-polymerase chain reaction (RT-PCR) and a shortage of test kits have led to consider chest computed to...
Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images.
IEEE journal of biomedical and health informatics
Nov 10, 2022
A novel coronavirus disease (COVID-19) is a pandemic disease has caused 4 million deaths and more than 200 million infections worldwide (as of August 4, 2021). Rapid and accurate diagnosis of COVID-19 infection is critical to controlling the spread o...
Ferrobotic swarms enable accessible and adaptable automated viral testing.
Nature
Nov 9, 2022
Expanding our global testing capacity is critical to preventing and containing pandemics. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are requi...
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