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Artificial intelligence
can improve health care by analyzing data from apps, smartphones and wearable
technology
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Your next doctor could very well be a bot. And
bots, or automated programs, are likely to play a key role in finding cures for
some of the most difficult-to-treat diseases and conditions.
Artificial intelligence is rapidly moving into
health care, led by some of the biggest technology companies and emerging
startups using it to diagnose and respond to a raft of conditions.
Consider these examples:
-- California researchers detected cardiac
arrhythmia with 97% accuracy on wearers of an Apple Watch with the AI-based
Cariogram application, opening up early treatment options to avert strokes.
-- Scientists from Harvard and the University of
Vermont developed a machine learning tool -- a type of AI that enables
computers to learn without being explicitly programmed -- to better identify
depression by studying Instagram posts, suggesting "new avenues for early
screening and detection of mental illness."
-- Researchers from Britain's University of
Nottingham created an algorithm that predicted heart attacks better than
doctors using conventional guidelines.
While technology has always played a role in
medical care, a wave of investment from Silicon Valley and a flood of data from
connected devices appear to be spurring innovation.
"I think a tipping point was when Apple
released its Research Kit," said Forrester Research analyst Kate McCarthy,
referring to a program letting Apple users enable data from their daily
activities to be used in medical studies.
McCarthy said advances in artificial intelligence
has opened up new possibilities for "personalized medicine" adapted
to individual genetics.
"We now have an environment where people can
weave through clinical research at a speed you could never do before," she
said.
- Predictive analytics -
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Some the same artificial
intelligence techniques used in the Google DeepMind Challenge to defeat a
grandmaster in the board game Go can be adapted for medical uses
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AI is better known in the tech field for uses
such as autonomous driving, or defeating experts in the board game Go.
But it can also be used to glean new insights
from existing data such as electronic health records and lab tests, says Narges
Razavian, a professor at New York University's Langone School of Medicine who
led a research project on predictive analytics for more than 100 medical
conditions.
"Our work is looking at trends and trying to
predict (disease) six months into the future, to be able to act before things
get worse," Razavian said.
-- NYU researchers analyzed medical and lab
records to accurately predict the onset of dozens of diseases and conditions
including type 2 diabetes, heart or kidney failure and stroke. The project
developed software now used at NYU which may be deployed at other medical
facilities.
-- Google's DeepMind division is using artificial
intelligence to help doctors analyze tissue samples to determine the likelihood
that breast and other cancers will spread, and develop the best radiotherapy
treatments.
-- Microsoft, Intel and other tech giants are
also working with researchers to sort through data with AI to better understand
and treat lung, breast and other types of cancer.
-- Google parent Alphabet's life sciences unit
Verily has joined Apple in releasing a smartwatch for studies including one to
identify patterns in the progression of Parkinson's disease. Amazon meanwhile
offers medical advice through applications on its voice-activated artificial
assistant Alexa.
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Watson Health, whose
Cambridge, Massachusetts office is shown in this photo, is also part of the
artificial intelligence health movement
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IBM has been focusing on these issues with its
Watson Health unit, which uses "cognitive computing" to help
understand cancer and other diseases.
When IBM's Watson computing system won the TV
game show Jeopardy in 2011, "there were a lot of folks in health care who
said that is the same process doctors use when they try to understand health
care," said Anil Jain, chief medical officer of Watson Health.
Systems like Watson, he said, "are able to
connect all the disparate pieces of information" from medical journals and
other sources "in a much more accelerated way."
"Cognitive computing may not find a cure on
day one, but it can help understand people's behavior and habits" and
their impact on disease, Jain said.
It's not just major tech companies moving into
health.
Research firm CB Insights this year identified
106 digital health startups applying machine learning and predictive analytics
"to reduce drug discovery times, provide virtual assistance to patients,
and diagnose ailments by processing medical images."
Maryland-based startup Insilico Medicine uses
so-called "deep learning" to shorten drug testing and approval times,
down from the current 10 to 15 years.
"We can take 10,000 compounds and narrow
that down to 10 to find the most promising ones," said Insilico's Qingsong
Zhu.
Insilico is working on drugs for amyotrophic
lateral sclerosis (ALS), cancer and age-related diseases, aiming to develop
personalized treatments.
- Finding depression –
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IBM is using its Watson
supercomputer, seen in this file picture, as part of a broad effort to help
medical research and health care through its Watson Health division
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Artificial intelligence is also increasingly seen
as a means for detecting depression and other mental illnesses, by spotting
patterns that may not be obvious, even to professionals.
A research paper by Florida State University's
Jessica Ribeiro found it can predict with 80 to 90% accuracy whether someone
will attempt suicide as far off as two years into the future.
Facebook uses AI as part of a test project to
prevent suicides by analyzing social network posts.
And San Francisco's Woebot Labs this month
debuted on Facebook Messenger what it dubs the first chatbot offering
"cognitive behavioral therapy" online -- partly as a way to reach
people wary of the social stigma of seeking mental health care.
New technologies are also offering hope for rare
diseases.
Boston-based startup FDNA uses facial recognition
technology matched against a database associated with over 8,000 rare diseases
and genetic disorders, sharing data and insights with medical centers in 129
countries via its Face2Gene application.
- Cautious optimism -
Lynda Chin, vice chancellor and chief innovation
officer at the University of Texas System, said she sees "a lot of
excitement around these tools" but that technology alone is unlikely to
translate into wide-scale health benefits.
One problem, Chin said, is that data from sources
as disparate as medical records and Fitbits is difficult to access due to
privacy and other regulations.
More important, she said, is integrating data in
health care delivery where doctors may be unaware of what's available or how to
use new tools.
"Just having the analytics and data get you to step one," said Chin. "It's not just about putting an app on the app store."
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