AI knows if you will get COVID-19 vaccine

UC researchers create predictive tool for vaccine hesitancy highlighted a new artificial intelligence tool developed at the University of Cincinnati that can predict with accuracy whether someone is willing to be vaccinated against COVID-19 or other diseases.

The relatively simple assessment one day could help public health officials anticipate regional spikes in disease based on vaccine hesitancy in the population.

A team led by researchers in UC's College of Engineering and Applied Science created a predictive model using an integrated system of mathematical equations describing the lawful patterns in reward and aversion judgment with machine learning.

The study demonstrates that artificial intelligence can make accurate predictions about human attitudes with surprisingly little data or reliance on expensive and time-consuming clinical assessments.

“We used a small number of variables and minimal computational resources to make predictions,” said lead author Nicole Vike, a senior research associate in UC’s College of Engineering and Applied Science.

“COVID-19 is unlikely to be the last pandemic we see in the next decades. Having a new form of AI for prediction in public health provides a valuable tool that could help prepare hospitals for predicting vaccination rates and consequential infection rates.”

The project was a collaboration between UC and Northwestern University.

Read the story.

Featured image at top: A UC College of Pharmacy student draws a syringe during a drive-through vaccination clinic at UC Health. Photo/Colleen Kelley/UC Marketing + Brand

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