NEW YORK, Feb. 23, 2016 /PRNewswire/ -- Arria NLG (LSE:
NLG) Arria NLG's Professor Ehud
Reiter, Chief Scientist at Arria NLG, will be discussing
ways in which Artificial Intelligence can impact the healthcare
ecosystem at the IBM Watson Health event on Thursday, March 3.
Leading organizations around the world are collaborating to
address the intersection of healthcare and how artificial
intelligence, and emerging technologies such as Natural Language
Generation (NLG) have the power to improve the existing healthcare
ecosystem.
NLG is a form of artificial intelligence software, specialized
in extracting information from complex data sources and
communicating that information in natural language (i.e. as if
written by a human). This technology provides healthcare with
intelligent reporting assistants to communicate what the data is
telling us in a quicker, more efficient and user-friendly way. NLG
technology can empower healthcare professionals and patients with
new insights about the patient's health and treatment.
Three key NLG uses Professor Reiter believes could transform the
current system include:
- Empowering patients
Every healthcare system in the world knows that the best way to
improve health is to encourage patients to do more for themselves,
including following healthier lifestyles, better self-management of
chronic conditions, and good compliance with treatment regimes. NLG
is a key tool in empowering patients, as it can explain complex
information in an understandable and sensitive manner. For example,
many diabetics have sensors which measure blood sugar levels, but
they struggle to use this information to manage their diabetes
because they often don't understand it, and can overreact and
indeed panic when they see their blood sugar change. An NLG
system can explain and contextualize any changes in blood sugar and
help diabetics respond appropriately.
- Empowering clinicians
Currently clinicians spend a great deal of their time writing
routine clinical documents such as referral letters, radiology
reports, shift handovers, and discharge summaries. This is
inefficient (we want doctors to be looking after patients, not
writing reports). Furthermore, human-written reports may contain
mistakes and be written in different ways by different clinicians;
poorly-written reports can also increase legal liability and
regulatory risks. It's much more efficient to get an NLG system to
generate draft reports, and ask clinicians to review these reports
and add any key medical insights.
- Improved decision-making
NLG can also be used to support clinical decision-making. In a
research project called Babytalk, NLG software generated summaries
of electronic patient record data for doctors and nurses in a
neonatal intensive care unit (NICU). Clinicians in the NICU could
see graphs of patient data, but the hospital was concerned that
some clinicians were not effectively using these graphs.
Experimental work suggested that NLG-generated written summaries of
data could be a useful addition to standard data visualizations,
for both real-time decision-making and longer-term care planning.
In particular, the NLG summary texts could prevent mistakes by
highlighting important information that was not obvious from the
visualization.
Insights about the individual, developed through the analysis of
data, can help identify risk factors, promote health and drive more
effective, early engagement from the entire community of care. But
there is a growing shortage of analytical talent.
With the use of NLG, clinicians can make more effective usage of
data, reduce the amount of time they spend on writing up reports,
and reduce the risks of mistakes due to information not being
passed from one clinician to another. Patients can now have a
personalized summary of their medical condition, in a language they
can understand, which is oriented to support key decision-making.
With the understanding that NLG provides, patients will feel
empowered and in control, and ultimately more satisfied with
care.
Professor Reiter will be speaking about the best use cases for
NLG, and what it could mean for the healthcare ecosystem, as part
of his lecture.
To learn more about Arria NLG, visit arria.com
Media Contact: Sharon Daniels +1
973-820-7005
Sharon.daniels@arria.com
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SOURCE Arria NLG