Artificial Intelligence

A new JAMIA study found that more than 6 million messages related to COVID-19 were sent using the Watson Assistant platform between March 30 and August 10 of this year.

This week's top stories include CMS adding more than 60 telehealth services but the American Telemedicine Association expressing concerns about remote patient monitoring, and DeepMind AI's protein folding prediction achieving unprecedented accuracy.

The machine learning-powered tech will be a "key component of our go-forward analytics and digital identity strategy," says CEO Gus Malezis.

A new study examined past vaccine uptake rates for flu and H1N1, and found that inoculation efforts fell short. The feds must help bridge that gap, "particularly for high-risk populations and communities of color," said former ONC chief David Blumenthal.

The New York health system has made AI and automation central to its mission, embedding algorithms into a wide array of workflows to target dozens of improvement initiatives.

Having the algorithms is the only way to deal with overwhelming amounts of data and a huge influx of COVID-19 patients, says Adam Myers.

Jonathan Weiner, professor at Johns Hopkins Bloomberg School of Public Health, details the data fundamentals that are necessary for effective AI and machine learning algorithms.

From genetic sequencing to symptom tracking to vaccine development, machine learning algorithms have been instrumental in helping uncover hidden clues about the novel coronavirus, says Cris Ross.

Biased algorithms are bad for patients – but with more awareness of potential AI disparities, experts say there's reason for optimism.

At the HIMSS Machine Learning and AI for Healthcare Digital Summit, experts said effective data governance requires visibility and clear ownership.