By 2025, 90% of U.S. hospitals will use artificial intelligence to save lives and improve their quality of care. This should come as no surprise to anyone in the industry. AI reduces the human effort spent on administrative and analytical tasks, empowering physicians and hospitals to focus on areas which truly require human intervention. In fact, half of U.S. hospital executives are actively investing in new AI applications. Efficient AI solutions already save hospitals millions of dollars every year, but we’ve only just begun to see their potential impact. Robots might not replace doctors, but hospitals equipped with AI tools willoutperform non-AI driven hospitals—and soon. Investing in AI-driven healthcare presents a significant opportunity for early adopters. Right now, we’re at the sweet spot: there is enough proven technology on the market to confidently invest on the ground floor, but we’ve still only scratched the surface of future AI applications.

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Healthcare executives: Don’t fear Artificial Intelligence.
Embrace it
By.Dr.Mahboob ali khan Phd
By 2025, 90% of U.S. hospitals will use artificial intelligence to
save lives and improve their quality of care.
This should come as no surprise to anyone in the industry.
AI reduces the human effort spent on administrative and
analytical tasks, empowering physicians and hospitals to focus on
areas which truly require human intervention. In fact, half of U.S.
hospital executives are actively investing in new AI applications.
Efficient AI solutions already save hospitals millions of dollars
every year, but we’ve only just begun to see their potential
impact. Robots might not replace doctors, but hospitals equipped
with AI tools willoutperform non-AI driven hospitals—and soon.
Investing in AI-driven healthcare presents a significant
opportunity for early adopters. Right now, we’re at the sweet
spot: there is enough proven technology on the market to
confidently invest on the ground floor, but we’ve still only
scratched the surface of future AI applications.
So, which areas are ripe for AI disruption?
In this article, I will explore the top eight most exciting AI
innovations in healthcare. And if you want to stay ahead of the
curve, make 2018 the year when you experiment with one or more
of these ideas.
1. Automatically Monitor Patients in Intensive Care
New AI analytic tools can monitor patients to predict
complications at the earliest possible moment.
Inpatient monitoring is a significant resource drain: in some
hospitals, nurses spend more than 60% of their time monitoring
patients. Even with this oversight, postoperative complications
remain a significant cause of mortality in inpatient settings.

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AI augments specialist care by analyzing patient vitals and other
data to identify anomalies before they’re obvious to nurses and
doctors.
For example, aspiration pneumonia is a major risk for intubated
patients. To address this issue, an Israeli startup called Art
Medical produces sensor-enabled smart feeding tubes which
monitor patients for complications like pneumonia, without the
need for constant human oversight. At-risk patients trigger an
alarm which is sent to the central nursing station.
The Cleveland Clinic has also used Microsoft’s AI assistant,
Cortana, to monitor patients in the ICU. When an individual
patient’s data indicates a potential issue, the AI-assistant notifies
care providers. This allows clinicians to detect the earliest signs
of cardiac arrhythmia.
Robotic monitoring solutions like these reduce “alarm fatigue”
from false alarms, helping care providers manage their time
effectively. More importantly, they keep vulnerable patients from
slipping through the cracks. Within the next decade, smart
monitoring devices with the ability to flag at-risk patients are
set to become as ubiquitous as cardiac monitors.
Takeaway:
Want to get ahead of the game? Consider investing in intensive
care monitoring. This is big business; vast quantities of data can
be collected from in-hospital patients to improve the overall
quality and effectiveness of care. Plus, startups currently
operating in this space today have barely scratched the surface of
this technology’s potential.
2. Automate Patient Outreach with Chatbots
AI-powered chatbots will take over administrative tasks ranging
from referrals and patient satisfaction surveys to appointment
booking and billing.
Thanks to AI-equipped chatbots, anyone with a smartphone or
computer can be referred to a specialist, verify their insurance,

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describe health symptoms, and set up medical appointments
(and follow-ups) in advance.
Many of these applications have dramatic effects on both patient
outcomes and the provider’s bottom line.
Unlike human employees, well-trained AI is highly accurate and
can work around the clock. But it doesn’t stop there: specifically-
designed chatbots can save hospitals millions of dollars on top of
reduced labor costs.
For example, a single missed appointment costs the provider an
average of $200. Smart appointment booking, which can predict
no-shows before they happen, could collectively save U.S. clinics
and hospitals up to $150 billion annually.
Healthcare execs are rushing to implement these solutions to
reach more patients and take advantage of the efficiency of robot
medical assistants. And the numbers back it up: the AI chatbot
market is currently projected to hit $1.5 billion by 2024.
Takeaway:
Whether you buy an off-the-shelf chatbot for your healthcare
business or decide to invest in one, here’s one thing we are sure
about: no matter what you think now, in 5 years chatbots will be
a cornerstone of hospital management. It’s not a question of
whether this will happen, but a question of who has the foresight
to implement it today.
3. Improve Hospital Efficiency with AI Command Centers
Hospitals generate massive amounts of data that can be
leveraged with AI to increase operational efficiency.
As the U.S. moves towards value-based care models, hospitals
increasingly need to minimize lengths of stay to reduce costs.
Modern medical centers are also logistically complicated and
require sophisticated technology to manage resource allocation
and patient flow.
AI can help with both of these issues by streamlining care
management systems and finding potential inefficiencies in real
time.

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For example, Johns Hopkins Hospital uses an AI command
center equipped with predictive tools to make the hospital’s
operations more efficient. The system pulls together data from
multiple IT systems at once, prioritizing activity in specific
sections of the hospital based on need. This allows the hospital to
assign beds faster, discharge patients more quickly, and accept
more complex and time-consuming cases.
Operations-focused AI can also manage OR, Cath lab, and GI lab
scheduling. By predicting how much time each procedure will
take, these new apps reduce the amount of time high-volume
procedure rooms go empty. In addition to reducing wait times and
maximizing the use of operating rooms and lab facilities, AI
assistants reduce the likelihood that other surgeries will have to
be rescheduled unexpectedly. Because ORs and labs are often the
most lucrative aspects of a hospital system, making them more
efficient directly impacts your bottom line.
Takeaway:
Interested in leveraging hospital data to improve communication
and workflow efficiency? Consider looking into scheduling and
operations-focused AI. At DAP, we’re already working with
many companies building apps to streamline hospital
management; these solutions will only become more popular in
the coming years.
4. Remotely Monitor Chronic Conditions
Smartphone apps and wearable devices use AI to help monitor
patients with chronic conditions.
Many patients with chronic conditions can’t self-monitor outside
of the hospital. In the case of diabetes, this can mean repeated,
expensive hospital visits or even deadly blood sugar
crashes. Doctors, meanwhile, spend valuable time manually
monitoring these patients’ symptoms.
Tempo, a Dutch medical device company, replaces this process
with non-invasive stickers and an AI platform which can forecast
and manage blood glucose levels automatically—and remotely.
Strikingly, initial studies saw a 9% reduction in blood sugar

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lows in patients using these stickers compared to those
actively monitored by physicians.
Another startup, Sensely, also uses AI to monitor patients with
chronic conditions. Their application uses Bluetooth smart
devices to take patient vitals, flagging those potentially at risk and
helping them to book medical appointments.
Takeaway:
Such applications mark only the very beginning of massive
innovation in health tech. Physicians can treat virtually any
disease cheaper and more effectively with the help of AI-assisted
tools like these wearable devices and smartphone apps. If you’re
looking to get ahead of the game, consider looking into one of
these applications, or building your own.
5. Enhance Robotic Surgery & Improve Surgical Outcomes
AI applications improve the accuracy, safety, and efficiency of
both robotic and manual surgery.
In 1992, a 64-year-old man had a successful hip replacement
from RoboDoc, a robotic surgical tool. In the nearly three decades
since then, robot-assisted surgery has grown by leaps and bounds.
In fact, it is projected that by 2025, as much as 80% of surgical
procedures will be performed at least partially by robots.
Robotic surgery offers many well-known benefits, including the
ability to make microscopic stable movements and allow
surgeons to work remotely and perform minimally invasive
surgeries with shorter recovery times.
But what many don’t know is that the most common robotic
surgery applications are already partially automated using AI—
and this is one of the most promising areas for future innovation.
For example, the da Vinci system, the most well-known robotic
surgeon, uses computer-aided vision and reduces human hand
tremors from the surgeon controlling it using machine learning;
though it is the longest-running big player (FDA approved in
2000), other start-ups and research groups are also rapidly
innovating in this space.
In late 2017, the semi-autonomous surgical robot “STAR”
(Smart Tissue Autonomous Robot) actually outperformed

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surgeons on a tumor-removal task. Such advances will only
become more common as more investment and innovation takes
place within robotic-surgery.
Even when surgeons work without robotic assist, AI can help
automate and regulate surgical procedures to quantitatively assess
surgeons’ skills. It can also reduce human error by prompting
surgeons with safety checklists and suggesting actions to
streamline surgical processes.
Takeaway:
Robotic surgery is a relatively mature field in which AI
improvements are poised to make a significant and immediate
impact for those with the ability to research and design the tools.
Minimally invasive and outpatient surgeries fueled by these
technologies are already seeing massive growth worldwide.
In short, if you aren’t already among those actively investing in
AI-driven surgery, now is the time to begin looking into ways to
leverage the power of AI to improve surgical outcomes.
6. Strengthen Hospital IT Security
AI helps security systems identify critical issues using human
behavior and analytics.
90% of U.S. hospitals experienced a cyber attack within the last
two years. You read that correctly. Ninety percent.
The costs of these incidents are astronomical, and the loss of
institutional trust this causes is hard to overestimate. In the past
five years alone, security breaches have cost the healthcare
industry over 30 billion dollars. In the future, cybercrime will
only become more common as hospital systems and their data
move online and become more lucrative targets.
In simpler times, password systems and anti-virus software were
enough. Those days are long gone.
Healthcare environments make security upgrades particularly
challenging because data cannot simply be locked down;
clinicians, billing, and administrative staff all still need to access
patient records., Yet, breaches most commonly come from
internal sources.

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Luckily, AI applications are quickly expanding to meet IT
security needs. Smart software can augment traditional metrics
like passcodes with biometrics. AI can “learn” the patterns typical
of an IT system to model normal human behavior. When an
anomalous, potentially malicious pattern occurs in the system, the
AI app can identify this much faster than even a highly trained
employee, stopping attacks before they become a problem.
Some AI-driven IT security apps are already on the market (take,
for example, Cognetyx’s Ambient Cognitive Cyber Surveillance
and the more famous IBM’s Watson for Cybersecurity), and AI
internet security promises to be an area of rapid future growth.
According to Gartner, 75% of security software applications
will include AI features by 2020.
Takeaway:
Unfortunately, cyber attacks are a matter of if, not when.
Especially if you’re already innovating in the medical IT arena,
incorporating AI into your existing infrastructure is key to
proactively ensure that your systems are equipped to handle
future security threats, and keep sensitive patient data safe from
cybercriminals.
7. Discover New Drugs Faster
AI also has promising applications in drug discovery, which must
constantly outpace disease evolution.
Drug discovery is a complicated, time consuming, and expensive
process which requires constant biological discoveries of new
compounds. Only a small percentage of these compounds make
it through the testing process, which costs over 2.5 billion USD
per drug and takes up to a decade to complete.
AI promises to drastically reshape this entire process, and big
pharma companies are already signing multi-million dollar
contracts with AI startups to speed up the drug discovery
process.
Way back in 2015, Atomwise designed an AI drug-discovery app
which could predict how molecules are likely to stick together.
Using this method, they were able to discover two drugs that
could treat Ebola in a fewweeks instead of years.

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More recently, Pfizer partnered with IBM’s Watson in 2016 to
create an application which can read the enormous and rapidly
expanding body of cancer literature to identify possible
combinations of compounds which would not be obvious to
human readers.
Takeaway:
If you’re involved with pharmacological development and testing
processes in any way, consider investing in AI-supported drug
discovery methods in 2018. Drug discovery is already big
business, and likely to see continued demand as the need for new
antibiotic, epidemic-prevention, and cancer-treating drugs
accelerates. Even a small improvement in drug-approval rates
could mean several billion dollars in profit, and rapid response to
new disease strains could save millions of lives.
8. Use Machine Learning to Aid in Diagnostics and Clinical
Decision-Making
AI supercomputers can process tens of billions of medical images
or patient records in seconds. The end result? Enabling medical
professionals to make faster and more accurate decisions.
Diagnostics is one of the most expensive and complicated
processes in healthcare and is often prone to human error—with
potentially fatal consequences.
Due to its complexity, it has also proved difficult to automate.
However, vendors and major academic centers worldwide are
seeing success this year with a wide array of artificial intelligence
neural networks used for clinical diagnosis and decision-making.
The tech startup Aidoc uses AI to comb through hundreds of
brain CT scan slices per second, searching for irregularities
hundreds of times faster than a radiologist. Any anomalies it finds
are flagged as high priority for the radiologist. Even preliminary
descriptions of imaging and measurements of lesions can be
completed by the computer.
IBM’s Watson, one of the most famous supercomputing AI
applications, offers both an image-analysis solution and a
machine learning algorithm that pulls relevant information from

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medical records. Both of these products assist providers with
diagnosis and decision making.
Finally, Google’s DeepMind health project is developing
algorithms for use in health record aggregation; since individual
patient records become very large and include information from
a variety of sources over time, this technique improves
physicians’ ability to diagnose and monitor diseases based on
patient history.
Takeaway:
What does this mean for industry leaders in the U.S.? In short,
diagnostics is and will remain an area ripe for new investment and
innovation.
Beyond the economic benefits of AI implementation, these
algorithms can ease decision fatigue and the intense case burdens
of medical staff, allowing them to focus on the complex and
unusual cases which truly require creative human problem-
solving.
Adding AI to existing clinical procedures also promises to
substantially reduce human error. The end result: dramatically
improved patient outcomes.

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Bottom Line
In this article, we’ve covered some of the most promising areas
of AI investment and development in 2018, including:
• Automating patient monitoring with smart inpatient AI
applications
• Using chatbots to automate patient communication and
administrative tasks
• Managing hospital operations with centralized AI command
centers
• Monitoring chronic conditions with wearable devices and apps
• Enhancing robotic surgery
• Improving IT security to protect vulnerable and sensitive data
• Speeding up the drug-discovery process
• Augmenting clinical decision-making with AI image and record-
analysis algorithms
According to a recent journal article published in Brazilian
Radiology, “if AI is the new electricity, data is the new coal.”
Hospital systems generate millions of gigabytes of data every
single day. Using modern, artificially intelligent-driven solutions,
healthcare providers can leverage this virtually unlimited
information to provide cutting-edge, individualized, and precise
medicine.
Already, healthcare leaders are seeing significant savings from
implementing AI solutions to improve patient-doctor
communications, hospital administration, diagnostics, and
clinical decision-making. This year, we predict continued growth
with a tangible impact on patient health.