[COVID-19 UPDATE]: Using Machine Learning to Treat COVID-19

National Institute of Health resorts to technology to diagnose, treat, and monitor the novel coronavirus.

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Global pandemics, like COVID-19, have always been a serious threat to the existence of mankind. This isn’t the first time and certainly, won’t be the last. Researchers around the globe are combining their efforts to develop a sustainable vaccine. In this attempt, the use of AI and machine learning has produced some desirable results.

It is no secret that technological evolution is playing a major role in our fight against COVID-19, with the healthcare industry exploring the usage of Artificial intelligence and other Machine learning techniques to improve the quality of treatment.

Early experiments in Machine Learning presented promising results with respect to COVID-19. From predicting the risk of the infection and severity of a case to predicting treatment outcomes, ML is being applied in a lot of situations. The possibilities are endless.  Scientists believe that ML is vital in order to counter the pandemic. Perhaps with the right data set, skills, and research, ML can be used to save lives – now and in the future. In this regard, the National Institute of Health is pondering on the use-cases of ML for a breakthrough in COVID-19 research.

The National Institute of Health (NIH) is using Artificial Intelligence and Medical imaging under its newly launched Medical Imaging and Data Resource Center (MIDRC). The multi-institutional partnership led by the NIBIB, a member of the National Institute of Health, will develop innovative methods for early diagnosis and tailored care of patients with COVID-19. Bruce J. Tromberg, Ph.D., NIBIB Director stated:

This program is particularly exciting because it will give us new ways to rapidly turn scientific findings into practical imaging tools that benefit COVID-19 patients. It unites leaders in medical imaging and artificial intelligence from academia, professional societies, industry, and government to take on this important challenge.

The medical images of the diseased lungs and hearts will be examined thoroughly to identify the severity of the disease. Moreover, the patient’s response can be predicted thereby improving the chances of a favorable outcome.

The MIDRC intends to pursue innovative development and deployment of technology, including machine learning techniques. This will enable the fast and precise analysis of the status and extent of the disease. In addition, the MIDRC allows fast and scalable acquisition, interpretation, and dissemination of clinical data.

The National Institute of Biomedical Imaging and Bioengineering (NIBIB), which is a part of the National Institute of Health, researches on the creation of new tools which will enable the provision of personalized therapies and the early and fast detection of COVID-19 patients.

However, the collection and continuous evaluation of data rapidly and accurately will facilitate optimum patient treatment.

Guoying Liu, Ph.D., who is leading the scientific program of the NBIB, said that “This effort will gather a large repository of COVID-19 chest images.” Not only will this enable researchers to analyze lung and cardiac tissue images, but will also make them ask important study questions and to build a predictive COVID-19 imaging signature that can be distributed to healthcare providers.

Maryellen L. Giger, Ph.D., the A.N. Pritzker Professor of Radiology, Committee on Medical Physics at the University of Chicago, is leading the research. Along with her are co-investigators Curtis Langlotz, MD, Ph.D., and Adam Flanders, MD, from the Radiological Society of North America (RSNA), Paul Kinahan, Ph.D., from the American Association of Physicists in Medicine (AAPM), and Etta Pisano, MD, and Michael Tilkin, MS, from the American College of Radiology (ACR), Curtis Langlotz.
The diversity in expertise in the medical imaging community brought about by the Collaboration among the ACR, RSNA, and AAPM coupled with manifoldness in their security, access, and sustainability becomes the foundation of this collaboration.
Krishna Kandarpa, M.D., Ph.D.,  director of research sciences and strategic directions at NIBIB said,
This major initiative responds to the international imaging community’s expressed unmet need for a secure technological network to enable the development and ethical application of artificial intelligence to make the best medical decisions for COVID-19 patients. Eventually, the approaches developed could benefit other conditions as well.
As reported earlier, similar research is being conducted by The Massachusetts Institute of Technology (MIT)  which is exploring the use of Artificial intelligence to combat COVID-19. Other AI techniques such as machine learning algorithms are being used to make intelligent judgments in the process of vaccine development.
A research group was formed to analyze how AI, machine learning, the Internet of Things (IoT) and cloud computing are being deployed in various sectors. The group named C3.ai Digital Transformation Institute was established in March 2020, around the time when COVID-19 was declared as a pandemic. The group consists of top scientists and scholars worldwide in order to promote and fulfill the project’s goals.
An initial funding of $5.4 million was provided to support 26 projects which the consortium approved for battling the ill effects of COVID-19. Some of these projects are such as that of Dimitris Bertsimas’ project on building automated decision-making systems to enhance healthcare procedures.
It becomes imperative that we adapt to the changing circumstances and develop innovative ways to combat the pandemic, which is exactly what the healthcare industry is doing.

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