Welcome to the age of cognitive computing: where intelligent machines have moved from the realms of science fiction to the present day. This groundbreaking technology is driving advanced discoveries and allowing improved decision-making – resulting in better patient care

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Automation Advances
April 2016
COG · NI · TIVE / käg-nə-tiv (adjective): of, relating to or
involving conscious mental activities (such as thinking,
understanding, learning and remembering)
At present, both the healthcare and life sciences industries are
coping with upheaval triggered by various economic, societal
and industry influences. Traditional industry boundaries
are being eroded and the resulting healthcare ecosystem
is increasingly being challenged to prove the value of each
treatment by empowered consumers living in an ever-
expanding digital world.
To thrive amid the chaos of change, leaders in both sectors
must be smarter in how they approach data. While the digital
age has brought a massive amount of healthcare information
brimming with insights, organisations still struggle to unlock
its full potential. Take the genome of just one cancer patient
– this is equivalent to half a terabyte of data (see Figure 1)
(1). But, despite the explosive growth of information across
all industries, less than 1% of the world’s data is currently
analysed, according to IDC (2). So how can players in the
healthcare ecosystem fully harness the insights that reside in
this data – structured and unstructured – for discovery, insight,
decision support and dialogue, and for the ultimate benefit of
the patient? The answer is cognitive computing.
Let us first define what we mean by cognitive computing. It is
a new computation paradigm which offers various capabilities.
These include the ability to learn and build knowledge from
various structured and unstructured sources of information;
understanding natural language and interacting more
organically with humans; capturing the expertise of top
performers and accelerating the development of expertise in
others; and enhancing the cognitive processes of professionals
to help improve and elevate the quality and consistency of
decision-making across an organisation.
Executives in the healthcare ecosystem agree that cognitive
computing has the potential to radically change the industry.
Among sector leaders familiar with the technology, 84%
believe it will play a disruptive role, 81% think it will critically
impact the future of their business and 95% intend to invest
in cognitive capabilities. The numbers are even higher for
life sciences, with 94% of executives stating that cognitive
computing will have a disruptive role (3).
Taking all these factors into account, how specifically can the
ecosystem leverage cognitive computing to address issues
currently plaguing healthcare today? The cognitive computing
paradigm has three capability areas that explicitly address
the industry areas previously identified: discover, decide and
engage (see Figure 2).
Heather Fraser at
the IBM Institute for
Business Value
Rise of the
Machines
Welcome to the age of cognitive computing: where intelligent machines have
moved from the realms of science fiction to the present day. This groundbreaking
technology is driving advanced discoveries and allowing improved decision-making –
resulting in better patient care
60%
30%
10%
Exogenous
factors
Clinical factors
Genomics factors
1,100 Terabytes
6 Terabytes
0.4 Terabytes
Generated
per lifetime
Per lifetime
Per lifetime
Image:©IBMInstituteforBusinessValue
Figure 2: Three emerging capability areas for cognitive computing
Figure 1: Data generated for a single individual is growing with time,
but only a fraction of it is usable through traditional analytics
• Helps discover insights that perhaps could not
have been found by even the most brilliant
human beings alone
• Finds insights and connections and understands
the vast amounts of information available
• Visualises possibilities and validates theories
• Acts as a tireless agent providing expert
assistance to human language
• Makes conversation naturally, using
human language
• Understands consumers from past
history and bring context and evidence-
based reasoning to the interaction
• Offers evidence-based options and
reduces human bias
• Evolves continually toward more
accuracy based on new information,
results and actions
• Provides traceability to audit why a
particular decision is made

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Discovery Possibilities
Innovation is the lifeblood of the life sciences industry, but it is
challenged by existing skills and tools that are unable to cope
with new data sources. Healthcare discovery is also restricted
by the constraints of traditional capabilities.
Cognitive systems can help users find insights that perhaps
might not be found by even the most brilliant human beings.
Discovery involves finding knowledge and connections, and
understanding the vast amounts of information available
around the world.
Some discovery capabilities have already emerged – such as
in medical research, where robust bodies of information exist.
Here, advanced cognitive capacities have dramatically reduced
research and discovery time – from months to minutes. Baylor
College of Medicine, for example, uses cognitive computing
to accelerate the rate and quality of scientific findings, and
address the challenge of discovering personalised medicines
by automatically analysing thousands of scientific articles in the
area of gene interactions (4,5).
Fast forward to the future, and cognitive solutions could
enable more effective and timely matching of patients to
clinical trials by rapidly analysing their historical data across
all relevant trials. Evidence-based reasoning applied to both
inclusion and exclusion criteria for patients could help those
seeking participants for trials – while CROs conducting
additional analysis could determine whether their results
could be used for further research.
Professional Decision-Making
An ever-expanding amount of medical data presents exciting
prospects for improved decisions – but only a fraction of this
is currently utilised due to existing tool constraints. Decision-
making in the healthcare ecosystem can also be difficult due to
the complex regulatory environment within which healthcare
and life sciences operate.
Cognitive systems aid in decision-making and reduce human
bias by offering evidence-based options. They continually
evolve based on new information, results and actions.
Current systems perform more as advisors by suggesting
a set of options to human users, who ultimately make the
final decisions. Therefore, cognitive computing is not about
replacing the doctor or the researcher.
These systems are helping healthcare professionals
make more informed and timely decisions. For example,
Bumrungrad International Hospital in Thailand is using a
cognitive computing solution that rapidly analyses patient
data, fast-growing medical literature, guidelines from
world-class experts and the experience of specialists –
and then identifies personalised treatment options for
the clinician to consider (6). Future policies could enable
the exchange of healthcare information among various

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organisations in the ecosystem, while still protecting
privacy. Cognitive systems will have access to even more
historical data and analysis, making their recommendations
more and more effective.
Patient Engagement
Today’s consumers want more control over their health – as
well as more personalised and convenient care. A clear majority
of healthcare executives say they understand these demands,
but 54% are not satisfied with their ability to comprehensively
and quickly address patient concerns. For life sciences, 68% of
executives are concerned that they cannot deliver customised
experiences to their consumers (3).
Cognitive systems can fundamentally change the way humans
and technology interact, and significantly extend the capabilities
of the former by leveraging their ability to provide expert
assistance.These systems provide advice by developing and
bringing deep expertise to people in a timely, natural and usable
way. Here, they play the role of an assistant – albeit one who does
not require sleep. Additionally, such a system can consume vast
amounts of structured and unstructured information, reconcile
ambiguous and even self-contradictory data, and can even learn.
Because it is able to engage in dialogue with humans,
this software can understand patients based on their
past medical history and bring context- and evidence-
based reasoning to the user interaction. They can extract
additional knowledge from underlying plain text sources,
such as health conversations, activity data and health benefit
information. Today, these types of cognitive systems help
healthcare organisations offer engaging and personalised
recommendations to consumers. For example, Welltok’s
CaféWell Concierge is helping to individualise the health
experience, and empower consumers to make positive
changes to their lifestyles. In the future, cognitive systems
will likely incorporate free-form dialogue capabilities, which
could help the flow of information among individuals and
populations (7,8). For instance, patients could engage in
dialogue with the system, enabled by input from providers,
while doctors could more easily share patient information
with appropriate providers for treatment input. Others in
the ecosystem, such as nutritionists, could simply ask for and
receive patient history from the system and avoid requiring
them to supply the same information yet again. All these
interactions would be in natural language – making the
process easier.
Starting your Cognitive Journey
It is evident that cognitive computing holds huge potential
to provide significant business and economic value – and
ultimately help transform healthcare. So how could your
organisation benefit from this technology? To get started
on your journey, you should consider these three crucial
questions:
1. What is the cost to your organisation associated with
making non-evidence-based decisions, or not having
the full array of possible options to consider when
actions are being taken?
2. What benefit would you gain from being able to detect
hidden patterns locked away in your data? How would
this accelerate innovation?
3. What opportunities exist to create more engaging and
personalised experiences across the wider life sciences
ecosystem?
References
1. Palmer D, Oxford University’s big data and Internet of Things
project to ‘create the NASA of biomedicine’, 27 October 2014.
Visit: www.computing.co.uk/ctg/feature/2378000/oxford-
universitys-big-data-and-internet-of-things-project-to-create-
the-nasa-of-biomedicine
2. New digital universe study reveals big data gap: Less than 1% of
world’s data is analyzed; less than 20% is protected, IDC Digital
Universe Study, December 2012
3. Fraser H, Sarkar S and Zaharchuk D, A booster shot for health
and wellness: Your cognitive future in the healthcare industry,
IBM Institute for Business Value, September 2015.
Visit: www.ibm.com/iibv/cognitiveindustry for Healthcare and
new Life Sciences paper
4. Picton G, Study shows promise in automated reasoning,
hypothesis generation over complete medical literature, Baylor
College of Medicine News press release, August 2014
5. Vickers G, Computer guided science tool advances one step
further, Baylor College of Medicine News press release,
August 2015
6. IBM Watson for Oncology. Visit: www.bumrungrad.com/en/
horizon-cancer-treatment-center-chemotherapy-bangkok-
thailand/technology/ibm-watson
7. Welltok raises $22 million in series C funding, including IBM
investment to fuel watson-powered health app, IBM news
release, 12 February 2014
8. Hardawar D, How Welltok tapped IBM’s Watson to upgrade its
health optimization platform, Venture Beat, October 2014. Visit:
www.venture beat.com/2014/10/22/how-welltok-tapped-ibms-
watson-to-upgrade-its-health-optimization-platform
Heather Fraser leads the Life Sciences and
Healthcare team at IBM’s business think-
tank, the IBM Institute for Business Value,
where she has researched and published
thought leadership on the future of the life
sciences, healthcare, and the emergence of
the healthcare ecosystem. She is a registered pharmacist
with 30 years of experience in the global life sciences and
healthcare sectors, and has held positions across industry,
consultancy and community pharmacy. Heather holds an
MBA from the University of Warwick, UK.
Email: hfraser@uk.ibm.com
About the author