1.0
– Introduction to Health 4.0
Health
4.0 focuses on collaboration,
coherence,
and convergence – or connecting all available health information,
services, devices and people together in a more meaningful way. See
Global
Artificial Intelligence Network for 2040.
Future
Scenario: By 2040, a space-based global artificial
intelligence (AI) network of satellites will be put in place that
will monitor and help provide healthcare to people on Earth and in
colonies across our solar system on the Moon, Mars, and other
locations. The system will be linked to massive global health data
warehouses storing data from a wide range of health IT systems,
e.g. Electronic Health Record (EHR) systems, Personal Health
Records (PHR), Health Information Exchange (HIE) networks,
wearable fitness trackers, implantable medical devices, clinical
imaging systems, genomic databases and biorepositories, surgical
robots, health research knowledgebases and more. The space-based global AI system will monitor and analyze the health data gathered on all humans in real-time, detecting potential individual and public health issues. The global AI system will detect problems, diagnose them, send alerts to patients and their healthcare providers, and recommend treatment plans to resolve the healthcare issue. The system will also be interfaced to pharmacies, laboratories, health insurers, public health agencies, and other institutions as needed. The system will also be able to monitor a patient's progress, as well as adherence to recommended treatment plans. It will also seek to anticipate potential healthcare issues and provide preventive health and predictive health information tailored to each human. |
Evolution of Health IT Systems
The
following is a brief overview of the evolution and use of health
information technology in the US since the late 1960's:
-
Health 1.0 (1970's – 1990) = Modular Health IT Systems, e.g. Patient Registration, Billing, Pharmacy, Lab…
-
Health 2.0 (1990's – 2010) = Integrated Electronic Health Record (EHR) Systems + Personal Health Records (PHR) + Clinical Imaging
-
Health 3.0 (2015 – 2030) = Networked EHR Systems + Genomic Information + Wearable & Implantable Sensor Data
-
Health 4.0 (2030 – 2040's) = Global Networked EHR Systems + Artificial Intelligence + Convergence of all Technologies Above + Real-Time Global Data Collection & Analysis
As
we approach 2020, we
are currently in
the process of developing, and implementing Health
3.0 technologies
and solutions in
the US and other advanced nations across the globe. Preliminary
design and pilot testing of some
Health
4.0 solutions is
just beginning.
Looking
at
2040 and Beyond
Looking
ahead to when Health 4.0 systems will finally
start
rolling into place, keep
in mind
some of the following
predictions
for Healthcare and Health IT systems by
2050.
See
Health
2020-2050.
-
By 2050 we will see more instances of global pandemics and the spread of deadly diseases as a by-product of the skyrocketing growth and migration of the global population.
-
Rise of 'Regenerative Medicine', Genetic Engineering, Stem Cell Research, and the development of 'Human Augmentation' technologies will dramatically alter people's life spans and capabilities.
-
Use of biorepositories and genomic information systems will further transform healthcare and help lower costs.
-
Emergence of future knowledge driven global health platform and solutions will be based on 'open' standards and technologies.
Selected
Links
|
2.0
– Building a Global Artificial Intelligence Platform for Health 4.0
Futurist
Ray Kurzweil has predicted that computers will be as smart as humans
by 2030. By 2045, he claims 'artificial intelligence' systems may be
a billion times more powerful than our unaided 'human intelligence'.
Are you prepared for what this means?
In computer science, an ideal Artificial intelligence (AI) system is designed to mimic cognitive functions that humans associate with other human minds, such as “analyzing”, "learning" and "problem solving". Cognitive computers are self-learning artificial intelligence (AI) systems that can find patterns in massive collections of unstructured data and turn it into a presentable form for many others to use. For more detail, see Wikipedia. |
The
promise of Artificial
Intelligence (AI)
has always been just
beyond
the horizon, not
quite realistic yet still visible to our
imagination through
movies and literature. At
its
inception, AI was
initially deployed
for highly selective defense
or space exploration applications. However,
over time it has steadily advanced and has begun to be utilized in
many other industries, such as healthcare and manufacturing.
Artificial Intelligence (AI) and Data-Driven Medicine
Artificial
Intelligence (AI) and data-driven
medicine are
the next frontier
in the healthcare
revolution. Electronic
Health Record (EHR) systems have been widely adopted by all major
healthcare institutions across the US over the past decade. Now
state and local Health Information Exchanges (HIE) networks are being
deployed to allow access to data in the EHR systems by healthcare
providers
whenever or wherever it's
needed.
In
the meantime, consumers
have been
gradually starting to use Personal Health Record (PHR) systems that
contain their patient data from the
various EHR systems of
healthcare institutions where they have been treated. Now we are
seeing the growing use
of other healthcare technologies that are also gathering
and generating even
more personal health data,
e.g. wearable and
implantable devices, genomic information
systems and
biorepositories, clinical imaging systems, and more.
It
turns out that Medical
data is the
essential part of today's
comprehensive
healthcare systems.
However, processing and
analyzing the massive
quantity of data now being generated by the wide range of
converging health information technologies is almost too much to
handle. It is an area the healthcare industry is struggling to come
to grips with as it turns more and more to use of Artificial
Intelligence (AI) as the means to gain control of the growing
mountain of health related data.
Roughly every three years, the amount of medical data on the planet doubles in size. By 2020, it is expected to double every 73 days. |
It
is time to begin focusing more proactively on the design and
development of a 'global healthcare platform for 2040' built on
artificial intelligence (AI) technologies.
Artificial
Intelligence (AI) in Healthcare
Analysts
predict a tenfold growth of the use of artificial intelligence in
healthcare in the next five years, for everything from cancer
diagnosis to diet tips. According to Frost and Sullivan, healthcare
providers will spend $6 billion per year on artificial intelligence
tools by 2021. Google, IBM and Microsoft are all investing heavily in
healthcare and analysts predict 30 percent of providers will run
cognitive analytics on patient data by 2018.
See
Artificial
Intelligence:
There's Still Hope for the Human Race
Early
types of these type of
cognitive systems built
on artificial intelligence (AI) technologies have
already started
entering the market.
These include
'smart'
triage systems
that
check
patients’ symptoms against massive
health data
warehouses, then
advise
patients and providers what
they should do next. Artificial Intelligence (AI) systems
are also
being used to help consumers
when buying
health insurance, to
monitor biometric data from personal fitness trackers, analyzing
genomic data to predict and potential life-threatening diseases, and
much more.
Artificial
Intelligence
(AI)
is advancing rapidly and is in the process of transforming the face
of healthcare.
Just
a few of
the many
areas in which
AI is being used to affect practice management and healthcare
services include
Diagnosis
and Treatment,
Disease
Management, Personal
Health & Wellness,
Utilization
Management & Reimbursement. Read
5
Ways AI is Changing Healthcare.
Other
areas where AI
technology and
data-driven systems can
be designed, developed, and used to improve healthcare include:
-
Examining and analyzing genomic data on hundreds of millions of patients.
-
Building systems that gradually teach themselves to become more accurate in its diagnosis.
-
Improving the speed and accuracy of diagnosis for genetic diseases.
-
Unlocking the possibility of personalized preventive and medical treatment plans.
-
Regularly monitor patients’ biometric data to see they are complying with their treatment plans.
-
Helping healthcare providers deliver better low-cost, evidence-driven care to consumers.
-
Helping consumers to avoid costly visits to doctor offices and hospitals.
-
Giving everyone in the world the equivalent of a doctor in their pocket – or smartphone.
Future
Scenario: By 2040, a space-based global artificial
intelligence (AI) network of satellites will be in place that will
monitor and help provide healthcare to people on Earth and in
colonies across our solar system, e.g. Moon, Mars. The system will be linked to massive global health data
warehouses storing data from a wide range of health IT systems, e.g. EHR, PHR, HIE, IoT devices... The global AI system will monitor and analyze the health data gathered on all humans in real-time, detecting potential individual and public health issues. The system will detect problems, diagnose them, send alerts to patients and their healthcare providers, diagnose the problems and recommend treatment plans to resolve the healthcare issue. The system will also be interfaced to pharmacies, laboratories, health insurers, public health agencies, and other institutions as needed. |
Current
News & Activities
The
following are a few selected articles you might want to read to get a
better handle on the latest news about current activities related to
Artificial Intelligence (AI) in healthcare:
-
65+ Artificial Intelligence Startups In Healthcare - CB Insights From 'Virtual Nurses' to drug discovery, this article identifies more than 65 Artificial Intelligence (AI) Startups in Healthcare as of 2016.
-
Top-5 Artificial Intelligence (AI) Companies in Healthcare – 2016 There are quite a few artificial intelligence (AI) companies in healthcare already. CB Insights recently identified 65 of them at various stages of funding. The five AI companies on that list which have raised $40 million or more are described in this article by Nanalyze.
-
A new day is coming in healthcare, where AI will help diagnose and treat patients In 2013, Jeopardy! fans were blown away as IBM’s supercomputer WATSON wiped the floor with longtime champion Ken Jennings. Now Watson Health AI is being used in 16 cancer institutes across the country, helping to diagnose and treat patients. Meanwhile, Google has launched DeepMind Health to create innovative new apps for healthcare professionals alerting them to patient emergencies and the risk of complications when considering possible treatment options.
Selected
Issues
The
following are some of the key issues that need to be addressed as we
continue moving forward with the design, development, and use of AI
technologies and data-drive healthcare information systems:
-
Ethics - This emerging issue is concerned with the moral behavior being programmed by humans into robots and other 'smart' machines, i.e. Roboethics.
-
Privacy & Security – This is always a key issue. When AI systems are turned loose to monitor all health information systems gathering data on all facets of your personal health, concerns about who has access to the data and who it is being shared with are just a few of the issues that must be adequately addressed upfront.
-
Jobs - The Bank of England has predicted that intelligent machines might take over 80 million American and 15 million British jobs, respectively over the next 10 to 20 years. The healthcare industry will not be immune to this change.
-
Legal Issues - One of the most important points of interest that needs to be hammered out first is the legality of these machines. When a doctor's gross negligence leads to a misdiagnoses and patient harm, the fault is placed squarely on the shoulders of the offending physician. But what happens when a similar situation befalls an AI system? If such a program were to misdiagnose a patient, who's to blame?
- Open Source - Many new 'open source' tools are arriving that can now run on affordable hardware and allow individuals and small organizations to perform prodigious data crunching and predictive tasks. Read about H2O, OpenAI, and other machine learning and AI tools being used in healthcare at Open Health News.
Regenstrief Institute and Indiana University School of Informatics & Computing, recently examined open source algorithms and machine learning tools in public health reporting: The tools bested human reviewers in detecting cancer using pathology reports and did so faster than people. Indeed, more and more healthcare systems on the cutting edge are looking at ways to harness the power of AI, cognitive computing and machine learning. See Artificial intelligence and cognitive computing - Healthcare IT News |
Recommended
Next Steps
Artificial
Intelligence (AI) systems today can learn in ways society once
thought impossible, which has major implications for multiple
industries –
especially the healthcare industry. It
is now
time
to begin focusing more proactively on a
public-private sector collaboration to
design and develop a 'global healthcare platform for 2040' built on
artificial intelligence (AI) technologies.
Many
countries are beginning to support the idea of having a global
healthcare network of data centers coupled with a state-of-the-art AI
technology platform that will allow sort through all the data,
standardize it, and put it into a form that is useful and easily
understood by patients, healthcare providers, healthcare insurers,
researchers, and other individuals and organizations.
Any
such global effort should keep in mind the key management strategies
for success in the 21st
century – Collaboration, Open Solutions, and continuous Innovation
(COSI). Building such a
global solution will require a massive global public-private sector
partnership. Think of all the
components that will need to converge to compose such a global
solution – e.g. healthcare technologies, research, knowledge,
organizations, and more.
One
final note, advances in AI and technology are helping create a
futuristic human-to-machine and machine-to-human interaction that can
best be described as an 'Invisible' User Interface (IUI) of
the future that simply works non-stop in the background to monitor
and improve health for everyone. It will just be there – serving
mankind.
Recommended
Links
Companies
Systems
& Projects
News
Sites
|
Associations
Journals
|
3.0
- Invisible
User Interface (IUI)
for
Health 4.0
The
Invisible User Interface (IUI) will be a key characteristic of next
generation Health
4.0
systems.
The
emerging Invisible
User Interface (IUI),
also referred to as the Natural
User
Interface
(NUI),
involves
a major paradigm
shift in man machine interaction using
a computer
interface
that will
be
basically
invisible. Most
computer interfaces today
use
artificial controls
and
tangible
devices
whose operation has to be learned, e.g.
Windows, computer mouse, joystick.
That's
about to change big time with
the convergence of multiple modern technologies.
See
Wikipedia.
The
Invisible
User
Interface
(IUI)
will
include
sound, touch, gesture, and
tactile
inputs and outputs as
humans interact
with an
ever increasing numbers of
'smart'
machines
all
around us,
i.e.
Internet of Things (IoT).
The goal for system developers is to now make
ubiquitous computing technology ever more simple to use – designing
systems to seemingly be more intuitive and accessible for use by
humans with minimal technical knowledge and expertise.
Health 4.0 -
Imagine a next generation Artificial Intelligence (AI) system
linked to a
massive global
health data warehouse storing data from a wide range of health IT
systems, e.g. Electronic Health Record (EHR) systems, Personal
Health Records (PHR), Health Information Exchange (HIE) networks,
wearable fitness trackers, implantable medical devices, clinical
imaging systems, genomic databases and bio-repositories, health
research knowledgebases, medical
sensors and
more. Health 4.0 Artificial Intelligence (AI) systems of the future will constantly monitor and analyze the health data gathered on humans in real-time, quietly detecting potential individual and public health issues in the background. It will detect problems and diagnose them, send alerts to patients and their healthcare providers, and generate treatment plans to resolve any healthcare issues. The system will also be interfaced to pharmacies, laboratories, health insurers, public health agencies, and other institutions as needed. The key is that most of this activity will be done quietly in the background. Health 4.0 systems will use a variety of emerging technologies that will allow an infrastructure of intelligent sensors embedded in our living and working environment to unobtrusively monitor your personal health data and then interact with you, your family, healthcare provider, and other concerned parties using a range advanced verbal and non-verbal communication technologies – think Amazon Echo or Apple's Siri personal assistants. |
Invisible
User Interface (IUI)
Today's
computers
can hear, see, read and understand humans better than ever before.
Using
advanced
ambient
intelligence devices embedded
in the environment where we live and work, these emerging
technologies will be able to monitor our
movements, voice, glances, and even thoughts – causing
these
systems to respond and
meet
our
needs in a variety of ways.
These
technologies are
opening a world of opportunities for
AI-powered
systems
to interact and serve us using next
generation Invisible User Interfaces
(IUI).
Think
about it! Our
words and natural
gestures will
trigger interactions with
computer systems and
the
Internet of Things (IoT) all around us,
just
as
if we
were
communicating to another person. Essentially,
we'll
be
doing away with old-fashioned 'screens',
today's
graphical user interface (GUI), and the
ever growing number of mobile
apps.
Building
the Invisible User Interface (IUI) is a
new way of approaching the user experience that thinks beyond the
screen. The goal is to
design systems to
better fit
within our
lives, rather than forcing us
to adapt to the machines
we use. Key features of
the IUI and future
systems include:
-
Anticipatory design of new products and experiences that use constantly available, real-time data to anticipate what customers need and want to do next.
-
Personalization is the way that companies can better connect and interact with their customers, giving them the information they need in a way that feels more 'human'.
-
Ambient communication involving an infrastructure of intelligent sensors that will be embedded in our living and working environment – including wearable and implantable systems.
-
Artificial Intelligence (AI) will be needed to monitor, analyze, and take action based on the wide array of data being collected on each person.
-
'Deep learning' is the process of teaching computers to understand and solve a problem by itself, rather than having engineers code each and every solution.
Examples of Systems using Invisible User Interfaces (IUI)
The
following are some
current examples
of emerging
next
generation apps
and
interfaces to tomorrow's information systems. What makes them special
is that they use
a non-traditional
invisible or
conversational user
interfaces
as their
means of interaction with
humans
-
Read
'No
UI'
Is The New UI.
-
Amazon Echo – Voice interaction device capable of accepting commands and providing a wide range of information to you upon request. It can also control smart devices in your home.
-
Braingate - Creating and testing transformative neurotechnologies to restore communication, mobility, and independence of people with neurologic disease, injury, or limb loss.
-
Emotiv – Creating mobile EEG wearable systems, providing access to advanced brain monitoring and cognitive assessment technologies. Read Telepathy and Brain Interface
-
Magic – This company provides access to a 'smart' personal assistant set of services to meet a range of customer needs.
-
'M' by Facebook - A personal assistant powered by artificial intelligence (AI) that’s integrated with Messenger to help complete tasks and find information on your behalf.
-
Wii – Uses a handheld pointing device for interacting with the Wii computerized game system that detects movement in three dimensions.
*
You might also want to explore Google
Glass, Hexoskin, and other
'smart'
wearable systems.
Conclusions and Next Steps
How
people communicate with each other is very different from how people
interact with machines. The
trend
in computer systems design now
involves
looking
more closely
at
how
humans
interact
and communicate
intuitively. The
goal is to
teach computers,
machines,
and
the Internet of Things (IoT)
to better
comprehend and communicate with humans.
‘The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.’ That’s what computer scientist Mark Weiser wrote in his famous article The Computer for the 21st Century, originally published in 1991. |
In
the relatively near future, we will be interacting with computers all
around us without noticing them. This ties in closely with the
Invisible User Interface (IUI) and the rapid growth of the Internet
of Things (IoT), which includes wearable, implantable, and
embedded health sensors.
Collaboration,
Coherence, and Convergence will be the key to industry efforts to
challenge the current generation of health IT and healthcare delivery
systems. Efforts are already underway to design and build the next
generation healthcare systems – Read Global
Health 4.0
for 2040 and Beyond
Other
Selected Links
|
Conclusion - Global
collaboration, 'open' solutions,
and convergence of the many innovative
technologies
currently under development are key for plans to build and deploy
Health 4.0 by 2040.
* Send us your suggestions and ideas on the development of Health 4.0
* Send us your suggestions and ideas on the development of Health 4.0