i3 - May/June 2019 - 14

Tech

By Susan Schreiner

C 4 T R E N DS

Five Ways AI is Transforming Health Care

AI, along with robotics, the Internet of
Things (IoT), 3D printing, genetic engineering and quantum computing are
converging and enabling new possibilities in health care and patient engagement. Global spending on health care AI
is expected to reach anywhere from $644
million to $126 billion by 2025.
Health care organizations and payers
are leveraging emerging technologies
while also dealing with challenges like
privacy, control of data, inequality and
bias. Let's look at a few key areas of focus.

and genetic information. Genetic testing is becoming easier and less expensive. The cost of sequencing one's entire
genome costs less than $1,000 via a
mobile app, as compared to over
$200,000 10 years ago.
Prescriptions and other treatment regimens based on a person's AI profile are
also moving away from a one-size-fits-all
category. Physicians can quickly identify
the most effective treatment, minimize
drug reactions and reduce the procedures they prescribe.

Top Five AI Health Trends

3. Leveraging AI for Diagnosis
AI is making its mark in health care delivery by reducing and/or removing the
potential for errors. In radiology, AI is
enabling radiologists to make more accurate diagnostic decisions, including breast
cancer. For example, two Massachusettsbased scientists created an AI system to
improve the detection and diagnosis of
lesions seen on mammograms.

CONTACT: Reach Susan at
susan@c4trends.com

measurements of health-related signs.
MIT's Computer Science and Artificial
Intelligence Laboratory is testing
Emerald, which offers promising "X-ray
Vision" technology. This smart home system uses AI, sensors and radio signals to
track movements, sleep, heart rate,
breathing and gait - as long as there is
Wi-Fi. Its radio signals bounce off a person's body, sending the reflection onto
the device's screen in the form of a stick
figure that walks, sits and moves its
limbs just as the person does.

5. Consumer Empowerment:
Virtual Doctors
With the help of AI, online apps give basic
1. Changing Expectations
health information and advice. There are
The challenge for AI is how to provide
AI-based services from insurers, for
better insight into medical data so that
instance, that serve as virtual doctors. If
health care consumers can make
you notice any symptoms, log into the app
informed health decisions. "Consumers
to get medical advice wherever you are.
expect health care to be available like conThe AI-driven system uses speech recogniducting their (online) banking, reserving
tion to help select the correct action by
their airline seats and making restaurant
analyzing data within the context of the
reservations," says Bernard J. Tyson,
consumer's health reports, but also exterchairman and CEO of Kaiser Permanente. 4. Health Monitoring and Wearables
nal research and clinical expertise.
Wearable devices are getting more
Imagine a world where AI can analyze
sophisticated, with sensors being inte2. Precision Medicine to
your health via eye scans, recognize
grated with algorithms that allow
Personalized Health
patients, doctors and anyone looking for depression, detect skin cancer and spot
Precision medicine will enable data to
outbreaks in disease so that people can
a healthier life to focus on prevention
screen for and treat disease, tailored to
and wellness. They generate continuous lead longer and healthier lives. It sounds
one's DNA via an AI profile that
like science fiction, but it's coming.
includes lifestyle, health history, biology data in real time, rather than periodic
14

MAY/JUNE 2019

I T I S I N N O VAT I O N

Natalya Burova/Getty Images

I is transforming the way we prevent, manage and treat illness in
new ways. It will maximize efficiencies and harness an increasing volume
of data and knowledge, but AI is different
from human intelligence. It uses machines
with algorithms to ingest and analyze
complex data. What distinguishes AI technology from traditional techniques in
health care is the ability to gain information and detect meaningful relationships
in data sets - for actionable output.

i3 - May/June 2019

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