The television show Jeopardy! inspired an IBM research team to build a supercomputer named Watson that successfully took

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The television show Jeopardy! inspired an IBM research team to
build a supercomputer named Watson that successfully took on the
challenge of playing Jeopardy! and beat the other human
competitors. Since then, Watson has evolved into a
question-answering computing platform that is now being used
commercially in the medical field and is expected to find its use
in many other areas.
Watson is a cognitive system built on clusters of powerful
processors supported by IBM's DeepQA® software. Watson employs a
combination of techniques like natural-language processing,
hypothesis generation and evaluation, and evidence-based learning
to overcome the constraints imposed by programmatic computing. This
enables Watson to work on massive amounts of real-world,
unstructured Big Data efficiently.
In the medical field, it is estimated that the amount of medical
information doubles every 5 years. This massive growth limits a
physician’s decision-making ability in diagnosis and treatment of
illness using an evidence-based approach. With the advancements
being made in the medical field every day, physicians do not have
enough time to read eve1y journal that can help them in keeping
up-to- date with the latest advancements. Patient histories and
electronic medical records contain lots of data. If this
information can be analyzed in combination with vast amounts of
existing medical knowledge, many useful clues can be provided to
the physicians to help them identify diagnostic and treatment
options. Watson, dubbed Dr. Watson, with its advanced machine
learning capabilities, now finds a new role as a computer companion
that assists physicians by providing relevant real-time information
for critical decision making in choosing the right diagnostic and
treatment procedures.
Memorial Sloan-Kettering Cancer Center (MSKCC), New York, and
WellPoint, a major insurance provider, have begun using Watson as a
treatment advisor in oncology diagnosis. Watson learned the process
of diagnosis and treatment through its natural-language processing
capabilities, which enabled it to leverage the unstructured data
with an enormous amount of clinical expertise data, molecular and
genomic data from existing cancer case histories, journal articles,
physicians' notes, and guidelines and best practices from the
National Comprehensive Cancer Network. It was then trained by
oncologists to apply the knowledge gained in comparing an
individual patient's medical information against a wide variety of
treatment guidelines, published research, and other insights to
provide individualized, confidence-scored recommendations to the
physicians.
At MSKCC, Watson facilitates evidence-based support for every
suggestion it makes while analyzing an individual case by bringing
out the facts from medical literature that point to a particular
suggestion. It also provides a platform for the physicians to look
at the case from multiple directions by doing further analysis
relevant to the individual case. Its voice recognition capabilities
allow physicians to speak to Watson, enabling it to be a perfect
assistant that helps physicians in critical evidence-based decision
making.
WellPoint also trained Watson with a vast history of medical
cases and now relies on Watson's hypothesis generation and
evidence-based learning to generate recommendations in providing
approval for medical treatments based on the clinical and patient
data. Watson also assists the insurance providers in detecting
fraudulent claims and protecting physicians from malpractice
claims.
Watson provides an excellent example of a knowledge-based DSS
that employs multiple advanced technologies.
Questions:
1. What is a cognitive system? How can it assist in real-time
decision making?
2. What is evidence-based decision making?
3. What is the role played by Wastson in the discussion?
4. Does Watson eliminate the need for human decision making?