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Preventing third wave of lockdown with Machine learning

New age technologies such as artificial intelligence and machine learning can predict and effectively prevent third wave of lockdown

Artificial intelligence and machine learning are technologies that almost everyone is now familiar with. These new age technologies are now a part of the daily lives of people. From making the right recommendations on songs one should listen to or shows that should be watched on OTT platforms to suggestions on what consumers need to buy from e-commerce, AI and ML are playing an important in almost every sector. In a similar vein, AI can play an effective role in combating and preventing the third wave of lockdown as well.

In this regard, Kundana Lal, president, Vitti Foundation addressed a webinar organised by MIT Centre for Future Skills Excellence-MITFUSE on how AI and ML can prevent a third wave of lockdown. The event was also addressed by Suraj Bhoyar, project director, MIT Centre for Future Skills Excellence. It is a known fact that the COVID-19 crisis has ushered in a new era of urgent innovation, which is leveraging and accelerating emerging technologies such as Artificial intelligence and machine learning, cloud, robotics, and data analytics. Lal addressed all aspects of how these technologies can be used to tackle the third wave.

How Artificial Intelligence Can be Used in Disease Management

Kundana Lal said that artificial intelligence has been used in several disease outbreaks earlier and can play a vital role in the fight against COVID-19. The following are the areas where AI can be applied to control the third wave:

  • Prediction and tracking.
  • Contact tracing.
  • Monitoring of COVID-19 cases.
  • Early diagnosis
  • Protein structure prediction.
  • Development of therapeutics.
  • Development of vaccines.
  • Curbing the spread of misinformation.
  • Genomics.
  • Reducing the burden from care-givers.

Lal further shared some artificial intelligence-based tools that have been adopted by countries to serve the purpose. For instance, BlueDot, a SaaS designed to track, locate and conceptualise infectious disease spread used big data to predict the COVID-19 pandemic. Furthermore, several countries launched AI-based contact tracing mobile applications, utilising technologies like Bluetooth, GPS, social graph, contact details, network-based API, mobile tracking data, card transaction data and system physical address.

Similarly, computer vision technology can be used in early diagnosis. Vitti in collaboration with Xvizn recently introduced an AI-based software COVIZN to alleviate the current need for quick identification of Covid-19 infection in lungs. The software has been validated by RML, New Delhi and AIIMS, Patna.

Also, DeepTracer, a program based on customised deep CNN, was used to derive protein complex structure of SARS-CoV-2 from high-resolution Cryoelectron microscopy density maps and amino acid sequence. Apart from software, the role played by Robots in the COVID wards to safeguard healthcare workers is known to everyone.

“AI has already impacted disease detection, social dynamic discussion, medical actions, and tracking actions. The onus lies on us to determine how AI can be leveraged in a more coordinated manner. We need to adopt a three-pronged approach based on testing, isolation and contact tracing to combat the COVID-19 pandemic,” said Lal.


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