Stanford researchers: Artificial intelligence is ripe for healthcare

Instead of envisioning AI outpacing humanity as we know it, researchers spot prime opportunities for clinical decision support, patient monitoring, surgery and more. 
By Jack McCarthy
09:08 AM
Stanford study artificial intelligence

When it comes to artificial intelligence, forget the scary movies about rebellious robots or the dire warnings of a dystopian world of disconnected humanity imagined by some popular writers. AI promises, rather, to change our lives in profound ways we are just beginning to experience, according to a ground-breaking survey produced by Stanford University.

Stanford is taking the long view of AI, with a project called One Hundred Study on Artificial Intelligence (AI100). The study, written by a panel of AI experts from multiple fields including healthcare, will continue as an ongoing activity, with periodic reports examining how AI will touch different aspects of daily life.

The first of those reports, "Artificial Intelligence and Life in 2030," looks into the effects that AI advancements will have on a typical North American city a little more than a decade from now. 

First off, contrary to the more fantastic predictions for AI in popular culture, the study panel found little cause for concern. “Instead, increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030,” the report said.

Particular to healthcare, AI promises a broad array of life-enhancing innovations that should be embraced.

“For AI technologies, healthcare has long been viewed as a promising domain. AI-based applications could improve health outcomes and quality of life for millions of people in the coming years — but only if they gain the trust of doctors, nurses, patients, and if policy, regulatory, and commercial obstacles are removed,” the panel of experts reported. 

[Also: Why machine learning is changing everything but healthcare

Prime AI applications include clinical decision support, patient monitoring and coaching, automated devices to assist in surgery or patient care, and management of healthcare systems.

Data is a key enabler, with advances in collecting useful data from personal monitoring devices and mobile apps, from electronic health records (EHRs) in clinical settings and, to a lesser extent, from robots designed to assist with medical procedures and hospital operations.

Progress, however, has not been as fast as initially imagined. 

“Using this data to enable more finely-grained diagnostics and treatments for both individual patients and patient populations has proved difficult, the panelists wrote. “Research and deployment have been slowed by outdated regulations and incentive structures. Poor human-computer interaction methods and the inherent difficulties and risks of implementing technologies in such a large and complex system have slowed realization of AI’s special purpose robots will deliver packages, clean offices, and enhance security, but technical constraints and high costs will continue to limit commercial opportunities for the foreseeable future.”

The removal of these obstacles has the potential to improve health outcomes and quality of life for millions of people over time.

Clinical settings
The report says the use of EHRs has not progressed smoothly. A limited number of vendors control the EHR market, and user interfaces are widely considered substandard. The promise of new analytics using data from EHRs, including AI, remains largely unrealized due to these and other regulatory and structural barriers. In the next fifteen years, AI advances, if coupled with sufficient data and well-targeted systems, promise to change the cognitive tasks assigned to human clinicians.  

[Also: AI, cognitive computing, machine learning are coming: Time to invest?]

“The opportunity to exploit new learning methods, to create structured patterns of inference by mining the scientific literature automatically, and to create true cognitive assistants by supporting free-form dialogue, has never been greater,” the report stated.

Healthcare analytics
AI’s ability to mine outcomes from millions of patient clinical records promises to enable finer-grained, more personalized diagnosis and treatment.

“Traditional and non-traditional healthcare data, augmented by social platforms, may lead to the emergence of self-defined subpopulations, each managed by a surrounding ecosystem of healthcare providers augmented with automated recommendation and monitoring systems,” the report said. These advances may radically transform healthcare delivery as medical procedures and lifetime clinical records for hundreds of millions of individuals become available.

Barriers to development remain, however. They include the slow pace of FDA approval of innovative diagnostic software and HIPAA requirements for protecting patient privacy that create legal barriers to the flow of patient data to applications that could utilize AI technologies.

mHealth
By combining social and healthcare data, some apps can perform data mining, learning, and prediction from captured data, though their predictions are relatively rudimentary. The convergence of data and functionality across applications will likely spur new and even obvious products, such as an exercise app that not only proposes a schedule for exercise but also suggests the best time to do it and, in turn, provides coaching to stick to that schedule.

Elder care
This category offers a variety of AI innovations. Smart devices in the home will help with daily living activities when needed, such as cooking and, if robot manipulation capabilities improve sufficiently, dressing and toileting. 

In-home health monitoring and health information access will be able to detect changes in mood or behavior and alert caregivers.

Personalized rehabilitation and in-home therapy will reduce the need for hospital or care facility stays.

The report concludes that significant AI-related advances have already had an impact on North American cities over the past fifteen years, and even more substantial developments are expected in the next fifteen, provided they are judiciously managed.

“Recent advances are largely due to the growth and analysis of large data sets enabled by the Internet, advances in sensory technologies and, more recently, applications of ‘deep learning,’” the report noted. “In the coming years, as the public encounters new AI applications in domains such as transportation and healthcare, they must be introduced in ways that build trust and understanding, and respect human and civil rights.” 

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