In this week's episode of CTC's Artificial Intelligence Series with Foley and Lardner, Antoinette Konski talks with Berkeley Professor Bin Yu on the ways machine learning and AI are being applied in health research, assisting the COVID effort, and how the human filter is being adapted to push research as quickly as possible.
Dr. Yu points out that the signal processing algorithms being used to combine data for the pandemic is very similar to the methods of combining data twenty years ago. In the pandemic case, a system was built and now data updates itself, then adds visualizations. To prep, humans have to do a lot of work to clean data, set automatic cleaning rules for future data imports, modeling, and more.
Over the next 5-10 years, Dr. Yu hopes the industry will develop more quality controls and standards, so data science becomes more accessible to a wider base of users. More users would have foundations in statistics so that people do not have to figure out details that could become shared frameworks.
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