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Machine Learning Model to Quicken COVID-19 Vaccine Release and More – Weekly Guide

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It has been months since the coronavirus pandemic has made lives difficult for people around the world. A vaccine for this deadly disease is the only hope for restoring normalcy and is awaited by one and all. In recent developments, MIT has developed a machine learning model to speed up the release of the coronavirus vaccine. In this weekly guide, we will discuss the same.

MIT develops machine learning model to quicken the release of COVID-19 vaccine

A new machine learning model has been developed by the researchers at MIT’s Computer Science and Artificial Intelligence Laboratory. This combinatorial ML system would be able to decrease the research time required for developing the vaccine and will make it more effective. 

The platform is called OptiVax and focuses on developing peptide vaccines. It is a different approach from the commonly followed whole virus, DNA, and RNA vaccines. The peptide vaccines are a recent development where the vaccine is developed around a specific short amino acid string called peptide that could be found in target disease. These peptides are synthetically developed in the laboratories, rather than being harvested from the disease/ virus itself.

Peptide vaccines are developed to eliminate the genetic elements that lead to unwanted immune responses and dangerous reactions. The traditional vaccines have large amounts of genetic information that is not useful for developing resistance and lead to unwanted responses. Peptide vaccines are also effective across a wider range of individuals. 

When it comes to COVID-19 vaccine, the researchers are trying to develop a complementary peptide targeting the spike proteins that cover the virus that can improve the effectiveness of traditional vaccines. The approach here is not to develop a pure peptide vaccine. 

Artificial intelligence helps Mumbai civic body detect 1,255 comorbid patients

The Brihanmumbai Municipal Corporation is working with Radical Health Private Limited to detect comorbidities and COVID-19 in patients. By analysing chest X-rays, CT scans, and retinal screening, Radical Health is helping BMC in early detection of COVID positivity and comorbidities in people.

Up until July 23, the start-up has successfully screened 3,167 patients out of which 1,255 had one or another comorbidity. Out of these 1,255 individuals, 65% were not aware of their comorbidities.

As those with comorbidities are more vulnerable to contracting a serious case of coronavirus, 88 individuals (2.78%) were marked in the high-risk category. 713 individuals (22.51%) were placed in the moderate risk category and 2,336 individuals (74.71%) were in the low-risk category. 

BMC’s public health department has sanctioned Radical Health-tech to work at the jumbo facilities along with the civic body as of July 24, 2020. 

Head to the Great Learning Academy for free courses on Artificial Intelligence and Machine Learning. 

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Great Learning Team
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