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Few know that Coronavirus and its allied disease Covid-19 was first discovered by a data-mining program. HealthMap, a website run by Boston Childrens Hospital, raised an alarm about multiple cases of pneumonia in Wuhan, China, rating its urgency at three on a scale of five. Soon after this discovery, the pandemic hit the world like a tsunami. As it progressed, Governments struggled to deal with the unprecedented crisis on multiple fronts and were forced to look at innovative ways to augment their efforts; presenting an opportunity to leverage Artificial Intelligence (AI).

AI was used in varied settings including drug discovery, testing, prevention and overcoming resource constraints, and its success opened a whole new door of possibilities. Heres a look at some of the most intuitive, innovative and advantageous uses of the technology during COVID-19, outlined under the four categories of diagnosis and prognosis, prediction and tracking, patient care and drug development:

Diagnosis and prognosis of COVID-19 using AI

AI assistance in prediction and tracking of Covid-19

AI-backed, superior care for COVID-19 patients

In Xinchang County, China, the drones delivered medical supplies to centers in need, and thermal sensing drones 14 identified people running fever, potentially infected with the virus.

Drug development with AI

There are several mechanisms, where AI accelerated the research on Covid 19. The key thing to note is much of the cutting-edge research is open source and thus available to the scientific and medical research community for further development or consumption.

Predictions for quicker vaccine development: Messenger RNA (mRNA) has a secondary structure that instructs cells to make proteins. Understanding the instruction and protein translation was key to the development of mRNA vaccine. However, mRNAs have a short half-life and degrade rapidly. This impacts the structural analysis of the virus. Access to quick viral structural analysis was significant to shorten the time it takes to design a potential mRNA vaccine with higher stability and better effectiveness, providing an opportunity to save thousands of lives.

Baidu AI team deployed Linearfold 2 , a model to predict the secondary structure prediction for the COVID-19 RNA sequence, reducing overall analysis time from 55 minutes to 27 seconds.Baidu also released the model for public use.

Challenges and the future of AI in health care

An AI solution must undergo a wide range of conditions and edge scenarios before it is deemed fit for use in terms of fairness, reliability, accountability, privacy, transparency, and safety. It also requires continuous monitoring of output vis--vis the everchanging real world, so it can learn from it.

Finally, policy formulation must support adoption of technology but tread with caution. FDA is actively working with stakeholders to define a comprehensive lifecycle-based framework that addresses the use of these technologies in medical care. This evolving framework differs significantly from FDAs own traditional regulatory control paradigm.

Artificial Intelligence has proved its value during the pandemic and holds much promise for mitigating future health care crises. However, this is just a start and the possibilities for intelligent care are limitless. This makes AI in health care an area of great opportunity for talented technologists who are also passionate about making an impact on people and communities through their work. Based on lessons learnt from the use of AI during the pandemic, policy makers, research institutes, businesses and technologists must incorporate these learnings as they chart the way forward.

Views expressed above are the author's own.

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Read more from the original source:

Humanitys fight against Covid: The promise of artificial intelligence - Times of India