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COVSeg‐NET: A deep convolution neural network for COVID‐19 lung CT image segmentation

#artificialintelligence

COVID-19 is a new type of respiratory infectious disease. It broke out for the first time in November 2019 and quickly swept the world in less than a year, posing a serious threat to world development and human survival. It is the most challenging problem facing the world today. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), which has caused high incidence rate and mortality worldwide.1 At present, the main clinical tool for the diagnosis of COVID-19 is reverse transcription polymerase chain reaction (RT-PCR), but the detection reagent is expensive and insufficient in quantity, and it needs specialized medical personnel to use it.2


Artificial Intelligence for COVID-19 Detection -- A state-of-the-art review

arXiv.org Artificial Intelligence

The emergence of COVID-19 has necessitated many efforts by the scientific community for its proper management. An urgent clinical reaction is required in the face of the unending devastation being caused by the pandemic. These efforts include technological innovations for improvement in screening, treatment, vaccine development, contact tracing and, survival prediction. The use of Deep Learning (DL) and Artificial Intelligence (AI) can be sought in all of the above-mentioned spheres. This paper aims to review the role of Deep Learning and Artificial intelligence in various aspects of the overall COVID-19 management and particularly for COVID-19 detection and classification. The DL models are developed to analyze clinical modalities like CT scans and X-Ray images of patients and predict their pathological condition. A DL model aims to detect the COVID-19 pneumonia, classify and distinguish between COVID-19, Community-Acquired Pneumonia (CAP), Viral and Bacterial pneumonia, and normal conditions. Furthermore, sophisticated models can be built to segment the affected area in the lungs and quantify the infection volume for a better understanding of the extent of damage. Many models have been developed either independently or with the help of pre-trained models like VGG19, ResNet50, and AlexNet leveraging the concept of transfer learning. Apart from model development, data preprocessing and augmentation are also performed to cope with the challenge of insufficient data samples often encountered in medical applications. It can be evaluated that DL and AI can be effectively implemented to withstand the challenges posed by the global emergency


So You Need Datasets for Your COVID-19 Detection Research Using Machine Learning?

arXiv.org Machine Learning

Millions of people are infected by the coronavirus disease 2019 (COVID-19) around the world. Machine Learning (ML) techniques are being used for COVID-19 detection research from the beginning of the epidemic. This article represents the detailed information on frequently used datasets in COVID-19 detection using Machine Learning (ML). We investigated 96 papers on COVID-19 detection between January 2020 and June 2020. We extracted the information about used datasets from the articles and represented them here simultaneously. This investigation will help future researchers to find the COVID-19 datasets without difficulty.


German Covid Easter U-turn shakes Merkel's cool, calm image

BBC News

Case numbers are rising exponentially, fuelled by the spread of the B117 or UK/Kent variant. Lothar Wieler of the Robert Koch Institute, which advises the government, has warned there are already indications that Germany's third wave could be worse than the first two. Without further action, he added, case numbers could soar to 100,000 a day.


Tammin Sursok says her husband has coronavirus but 'all the hospitals are full'

FOX News

Fox News Flash top entertainment and celebrity headlines are here. Check out what's clicking today in entertainment. "Pretty Little Liars" actress Tammin Sursok has revealed that her husband, Sean McEwen, is sick with coronavirus. She made the announcement on Instagram on Wednesday alongside a photo of herself looking somewhat teary-eyed. And I'm scared," she wrote in the caption. "Today I'm not as scared as yesterday but yesterday I felt very out of control.