Computer scientists and machine learning researchers are tackling the pandemic the way they know how: compiling datasets and building algorithms to hunt out out from them.
There’s already a dataset of COVID-19 cases on Google’s data science competition platform Kaggle, which is updated with new cases daily. the info is robust , including patient age, location, once they began to experience symptoms, once they were exposed, once they entered a hospital, and much of more. Nearly 300 people have used the info in their own analyses.
A researcher from the University of Montreal has collected and published a database of dozens of CT scans and chest X-ray images. the pictures are taken from publicly available studies on the disease.
And Johns Hopkins University has built a strong dashboard of well-sourced data that’s updated regularly, giving a worldwide inspect the spread of the disease and its mortality. It are often copied and modified because the code is out there on GitHub.
Other datasets have come directly from hospitals treating patients, which have quickly tried to point out around machine learning models to assist doctors trying to seek out signs of the disease.
Here are a number of those papers:
Lung Infection Quantification of COVID-19 in CT Images with Deep Learning:-
Shanghai researchers have devised a system that, alongside a person's checking the results, could reduce the analysis time of a CT image from hours right right right down to about four minutes.
Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis:-
This paper also claims to detect the presence of the COVID-19, but also visualizes the virus’s effects on the lungs to trace the progress of the illness over time.
Abnormal respiratory patterns classifier may contribute to large-scale screening of individuals infected with COVID-19 in an accurate and unobtrusive manner:-
Researchers here look for an auditory way of screening for COVID-19 by analyzing how briskly a private is breathing. The research isn’t conclusive, but it’s a replacement idea for a less invasive way of testing for the virus.
Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia:-
This work tries to differentiate the pneumonia suffered by patients with COVID-19 from the garden-variety flu.
Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan:-
Using nearly 3,000 electronic health records from patients in Wuhan, China, researchers built an algorithm that might predict the speed of mortality for patients with quite 90% accuracy.
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