Deep learning is putting the “care” back in healthcare.

“It used to be we just talked about deep sequencing. Now we talk about deep everything in medicine,” healthcare luminary Eric Topol told a packed audience Tuesday morning at the 10th annual GPU Technology Conference, in San Jose.

With advances in AI and healthcare, he said, medical professionals will need to spend less time entering and looking at data on computers. This will give them “the gift of time” to provide patients with personal care and bring back the strong doctor-patient bond that existed decades ago.

“A common enemy of the patient and the doctors and the nurses is the keyboard, because it interferes with their relationship,” he said. “It makes doctors data clerks.”

The founder and director of the Scripps Research Translational Institute, Topol released last week a new book, “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again.” His talk outlining how AI will transform everything doctors do was followed by a book signing.

“Every single type of health professional” will be impacted by AI, Topol said. Bringing AI into the medical workflow can help healthcare institutions provide “better, faster, cheaper” care by augmenting what clinicians can do.

“When you put the two together — machine algorithm plus the radiologist — you start getting a really winning combination.”

But humans will always remain integral to healthcare.

“We’re not going to get to the point where all medical diagnosis will not require human backup. Ever,” he said. “But we may get to a point where some of them, routine things like a sore throat or an ear infection or skin rash can be done completely algorithmically — both diagnosis and recommendations for treatment.”

Scripps Translational Institute focuses on genomics, a field that “is starting to go medical mainstream. Finally,” Topol said. NVIDIA and Scripps recently established a center of excellence for AI in genomics and digital sensors.

Topol showed initial results of the joint work, which included deep learning applications for genomics that improve accuracy, decrease costs and produce results faster.

“I said at the time that eventually, eventually, it would markedly improve accuracy, efficiency and workflow,” he said. “But I didn’t realize that just five months later, we’d do that. I thought it was going to take years.”

Healthcare at GTC

GTC features more than 40 healthcare sessions with innovators in AI and medicine, including:

• Brandon Fornwalt, associate professor and chair of the imaging science and innovation department at Geisinger, and Aalpen Patel, chair of Geisinger System Radiology
• Sunita Chandrasekaran, assistant professor at the University of Delaware
• Dima Rekesh, senior distinguished engineer, and Julie Zhu, chief data scientist and distinguished engineer, at Optum — the health services platform of UnitedHealth Group
• Rima Arnaout, assistant professor, and Christopher Hess, professor and chair of radiology and biomedical imaging, at the University of California, San Francisco
• Neil Tenenholtz, director of machine learning at the MGH & BWH Center for Clinical Data Science
• Tessa Cook, assistant professor of radiology at Penn Medicine
• Richard Tobias, CEO of Cephasonics Ultrasound Solutions
• Gerald Quon, assistant professor at the University of California, Davis

The full lineup of healthcare speakers at GTC, which runs through March 21, is available here.

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