A new report assessed how AI has helped address Covid-19 and where it has fallen short.
What’s new: Machine learning systems haven’t lived up to their promise in some areas, but in others they’ve made a substantial impact, biomedical engineer Maxime Nauwynck wrote in The Gradient, an online journal of machine learning.
Application areas: The author surveyed only systems specifically designed or adapted to fight Covid-19.
- Clinical Applications: In the pandemic’s early months, hundreds of research papers described systems allegedly capable of diagnosing the illness from lung scans. Few made it into clinical practice. Most were tripped up by poorly constructed public datasets, unexplainable output, or inadequate quality control.
- Epidemiology: Early AI models were hobbled by lack of data, but public health officials in the U.S. and UK ultimately developed ensemble systems to track the disease’s spread and anticipate its impacts.
- Treatments: The FDA granted emergency approval to treatments developed by biomedicine startups BenevolentAI and AbCellera. Both companies used AI to aid drug discovery. Moderna credits AI with helping it develop one of the first vaccines with extraordinary speed.
- Information: Chatbots helped overburdened health workers in China and the U.S. manage the deluge of patient questions, appointment scheduling, and other services.
- Public Safety: Computer vision systems are helping cities and businesses monitor social distancing. In France, systems detect whether individuals are wearing masks in public places.
Behind the news: AI-powered health monitoring systems from BlueDot and Healthmap made headlines early last year when they reported a novel disease outbreak in the Wuhan area one week before the World Health Organization issued its first warnings.
Why it matters: While AI is no panacea, this inventory makes clear that the technology has made significant contributions to the fight against Covid-19.
We’re thinking: When new technology meets a previously unknown illness, there are bound to be hits and misses. The successes should help us prepare for — or, better yet, avoid — the next contagion.