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November 30, 2021updated 30 Jun 2022 7:24am

Mixed results from use of artificial intelligence in helping combat Covid-19

Many artificial intelligence tools have been developed in response to the Covid-19 pandemic, but their results have been mixed.

By GlobalData Healthcare

As the Covid-19 pandemic unfolded, the world turned to one of its newer tools, artificial intelligence (AI), to help combat the spread of the disease. In an attempt to help doctors diagnose Covid-19 patients faster and more efficiently, hundreds of machine learning programmes and predictive tools were built by software developers worldwide. The results of these tools have been mixed at best.

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AI was utilised to help predict the effectiveness of potential Covid-19 drugs for specific targets, as it has been shown to help expedite drug development and reduce the risk of costly failures. AI can help researchers use diverse datasets in their analyses, which can help provide new insights and increase the predictive power of their programmes. The application of AI to drug programmes did show some successes. BenevolentAI was able to rapidly identify the rheumatology drug baricitinib as a potential repurposed Covid-19 treatment, and the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Laboratory was able to use deep learning algorithms to find two new drug combinations for treating Covid-19, namely remdesivir + reserpine and remdesivir + IQ-1S. Reserpine is an adrenergic blocking agent used to treat mild to moderate hypertension, while IQ-1S is a JNK inhibitor and displays strong antiviral SARS-CoV-2 synergy in vitro.

The creation of datasets and repositories in response to the pandemic has also facilitated increased sharing and collaboration across disciplines. Mobility datasets were made available by several commercial providers, including Google and Facebook, to model viral transmission, which helped provide evidence of the impact of lockdowns. The Turing Institute built Project Odysseus, which allowed for the monitoring of street-level activity based on traffic cameras and sensors. These data were used to help improve social distancing by moving bus stops or increasing pedestrian pavement widths. The Turing Institute also worked on the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative, which allowed for the comparison of various lockdown strategies using data on people’s activities.

Despite the successes in many instances, the use of AI has had some failures. Recent consensus by the UK’s Turing Institute is that few of these medical diagnostic tools had any impact, and some of them turned out to be harmful instead of helpful. An analysis of more than 230 algorithms that could be used to diagnose patients to predict future disease outcomes demonstrated that none of them could be used clinically, and only two of them showed enough promise for future testing. Another analysis of more than 400 deep-learning models for the diagnosis of Covid-19 by Cambridge University showed that none were fit for clinical use. These tools often faced issues because the datasets that were used to train the machine for learning the algorithms were also being used to test the algorithms.

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Free Whitepaper
img

What is the impact of China’s Zero-COVID lockdowns on economic activity, consumer goods and the foodservice industry?

While wanting to protect the country from being overwhelmed by Omicron, China’s adherence to a Zero-COVID policy is resulting in a significant economic downturn. COVID outbreaks in Shanghai, Beijing and many other Chinese cities will impact 2022’s economic growth as consumers and businesses experience rolling lockdowns, leading to a slowdown in domestic and international supply chains. China’s Zero-COVID policy is having a demonstrable impact on consumer-facing industries. Access GlobalData’s new whitepaper, China in 2022: the impact of China’s Zero-COVID lockdowns on economic activity, consumer goods and the foodservice industry, to examine the current situation in Shanghai and other cities in China, to better understand the worst-affected industry sectors, foodservice in particular, and to explore potential growth opportunities as China recovers. The white paper covers:
  • Which multinational companies have been affected?
  • What is the effect of lockdowns on foodservice?
  • What is the effect of lockdowns on Chinese ports?
  • Spotlight on Shanghai: what is the situation there?
  • How have Chinese consumers reacted?
  • How might the Chinese government react?
  • What are the potential growth opportunities?
by GlobalData
Enter your details here to receive your free Whitepaper.

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