Deep
learning, natural language processing (NLP), querying method and context aware
processing are some of the technologies used for AI in healthcare. The demand
for NLP in healthcare has been growing mainly due to rise in unstructured
clinical data. Since NLP technology extracts important clinical information
from unstructured data and analyze it for enhancing processing and analytics.
The
key factors that drive the growth of the industry include rise in need for
coordination between healthcare workforce and patients, increasing application
of Big Data in healthcare industry, ability of AI to improve patient outcomes,
growing demand for precision medicine and increase in venture capital
investments.
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With the increasing use of big data in healthcare sector, the vast amount of data can be stored systematically, as big data makes it easier for hospital staff to work efficiently. In order to monitor blood pressure, heartbeat and respiratory rate sensors are used besides patient beds which alert the doctors and hospital staff if any change is observed in the patient condition. Big data also help to fight cancer and mapping the 3 billion DNA base pairs during treatment of cancer. Big data improves hospital administration by reducing the cost of care measurement and provide best clinical support.
North
America leads the global market due to presence of major AI providers including
Intel Corporation, Google, Inc., IBM Corporation in the region. Other factors
leading the market growth include, developed healthcare infrastructure, and
growing aging population. Asia-Pacific is expected to witness the fastest
growth during the forecast period. Increasing healthcare expenditure,
continuously improving healthcare infrastructure due to growing medical tourism
and growing aging population are the factors expected to support the growth of
the Asia-Pacific AI in healthcare market.
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