ArtificiaI intelligence in the COVID-19 era

As part of his article on forbes.com ‘The 4 top artificial intelligence trends for 2021’, Bernard Marr talks about the innovation potential (and need), specifically coming apparent during the COVID-19 pandemic. He mentions that ‘The COVID-19 pandemic has impacted many aspects of how we do business, but it hasn’t diminished the impact artificial intelligence is having on our lives. In fact, it’s become apparent that self-teaching algorithms and smart machines will play a big part in the ongoing fight against this outbreak as well as others we may face in the future’.
 
He goes on and describes how our current technology ecosystem and data availability has helped reduced impact, offers insights and prediction capabilities, and stresses that the potential future applications will be beneficial in order to help detect and prevent future outbreaks of COVID-19 and other viruses. Below some takeaways from the writings that are very close to MUUTAA’s endeavour to predict the impact on the healthcare supply chain demand. I encourage you to read the complete post.
 
The need for accessible structured data.
 
‘By developing our ability to apply machine learning problem-solving to these massive, real-time global datasets, we will spot outbreaks more easily, track contact between infected people, enable more accurate diagnoses, and, by predicting ways that a virus might evolve in the future, develop more effective and lasting vaccinations.’ NLP applications processing scientific information and databanks become a crucial part in the prediction capabilities in future settings.
Automated detection tools.
 
Understanding behaviour and capabilities to track and trace human movements will become a more accepted and crucial part of the management of the outbreaks. As we are currently unfortunately still experiencing, the tracing and alerting capability are yet a time-consuming effort, where technological assistance can and will have a tremendous impact.
 
The ultimate predictive tool.
 
Mr. Marr describes the ultimate objective where the compounded information sources would be so efficiently interpreted, that any future outbreaks would be predicted well in advance and therefor would be controlled very early avoiding them to evolve to the pandemic level.
Foto: IEEE Spectrum

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