So much patient data – but what does it all mean? The health care industry is just beginning to realize the possibilities of artificial intelligence to transform care, according to a Thursday morning session at the U.S. News Healthcare of Tomorrow conference in the nation's capital.

Health and technology experts, moderated by Ike Swetlitz, a Washington correspondent at the health and medical publication STAT, delved into deep learning in clinical settings. The panel noted progress and barriers in areas such as digitalizing health care, improving medical imaging and solving ever-present problems like hospital falls.

It's impossible to incorporate AI into health care without addressing the human factor. The issue isn't about AI replacing health care workers and taking their jobs, emphasized Jeffrey Bundy, senior vice president of global strategy, business development and marketing for Siemens Healthcare. "The role of AI is going to make people's jobs [better], to give people information they don't have, so they can quantify things and do things they couldn't before," he said.

Making sense of the massive amount of existing health data and using it to optimize health care delivery poses a significant challenge, panelists agreed. "Now we have a data river – a large amount of data – but it's just not meaningful," said Deborah Muro, chief information officer for El Camino Hospital in California. Putting real-time data in the hands of providers helps them better help patients, she says.

One practical example: Building an algorithm to score and identify hospital patients at high risk of falls. By quickly capturing information like how often patients use call lights and get out of bed, nurses can be alerted in real time to check on patients and intervene to prevent falls, Muro said.

Better use of AI could improve health care by sharing data on much wider scale. "We're really banking on interoperability in Silicon Valley," Muro says. Ideally, data could be shared across the nation among all electronic medical records, she adds.