The first line of defense to prevent the spread of COVID-19 are non-drug measures such as social distancing and personal hygiene. This pandemic, which affects the lives of billions of people economically and socially, has prompted the scientific community to propose solutions based on computer-aided digital technology for the diagnosis, prevention and estimation of COVID-19. Some of this work focuses on statistics and artificial intelligence-based analysis of available data about COVID-19. All these scientific efforts require that the data used for analysis should be open source to facilitate the expansion, verification, and collaboration of efforts to fight the global pandemic.
The scientific community pooled their brains to come up with ideas that can limit crises and help prevent such epidemics in the future. In addition to medical science researchers and virology experts, with the support of digital technology, scientists have responded to the epidemic with new methods. In the fight against COVID-19, it can be determined that two important scientific communities are assisted by digital technology. The main digital work in this area comes from the artificial intelligence (AI) community in the form of automatic detection of COVID-19 from computed tomography (CT) scans and X-ray images. The second such community assisted by digital technology is mathematicians and epidemiologists who are developing complex virus transmission and transmission models to estimate the spread of viruses in various mobile and social distancing situations.
Artificial intelligence (AI) and machine learning (ML) technologies have been widely used to effectively solve various computer science problems from bioinformatics to image processing. Machine learning is based on the premise that an intelligent machine should be able to learn and adapt from its environment based on its experience, without the need for explicit programming. ML models and algorithms have been standardized across multiple programming languages such as Python and R.
The main
challenge of ML model application is the availability of open source
data. Given the publicly available data sets, machine learning
technology can help fight COVID-19 in many ways. The main content of
such applications is ML-based COVID-19 diagnosis through CT scan and
X-ray, which can alleviate the burden of shortage of reverse
transcriptase polymerase chain reaction (RT-PCR) test kits.
To put all the different types of data in perspective, image below is a quick Taxonomy of the types of COVID-19 related data.
 |
| Taxonomy of open data sources related to COVID-19 |
Chest CT scan and medical image in X-ray form It is essential for automatic COVID-19 diagnosis. artificial intelligence Motivated COVID-19 diagnostic technology can be equally accurate As a human, save the radiologist's time and make a diagnosis It is cheaper and faster than common laboratory methods.
 | |||
| Generic Workflow of use of AI/ML tools for use of image data for diagnosis |
The more the availability of open source data in the hands of the AI/ML experts better it is for all of us. Outside of pharmacological and treatment advances AI/ML offers the best and most effective way to combat this deadly global pandemic.
Follow all precautions, get vaccinated and lets all stay safe. Best of luck to us all!
References
The first line of defense to prevent the spread of COVID-19 are non-drug measures such as social distancing and personal hygiene. This pandemic, which affects the lives of billions of people economically and socially, has prompted the scientific community to propose solutions based on computer-aided digital technology for the diagnosis, prevention and estimation of COVID-19. Some of this work focuses on statistics and artificial intelligence-based analysis of available data about COVID-19. All these scientific efforts require that the data used for analysis should be open source to facilitate the expansion, verification, and collaboration of efforts to fight the global pandemic.The first line of defense to prevent the spread of COVID-19 are non-drug measures such as social distancing and personal hygiene. This pandemic, which affects the lives of billions of people economically and socially, has prompted the scientific community to propose solutions based on computer-aided digital technology for the diagnosis, prevention and estimation of COVID-19. Some of this work focuses on statistics and artificial intelligence-based analysis of available data about COVID-19. All these scientific efforts require that the data used for analysis should be open source to facilitate the expansion, verification, and collaboration of efforts to fight the global pandemic.The first line of defense to prevent the spread of COVID-19 are non-drug measures such as social distancing and personal hygiene. This pandemic, which affects the lives of billions of people economically and socially, has prompted the scientific community to propose solutions based on computer-aided digital technology for the diagnosis, prevention and estimation of COVID-19. Some of this work focuses on statistics and artificial intelligence-based analysis of available data about COVID-19. All these scientific efforts require that the data used for analysis should be open source to facilitate the expansion, verification, and collaboration of efforts to fight the global pandemic.