Artificial Intelligence in Healthcare: The Future is Cured
Artificial intelligence (AI) aims to mimic human
cognitive functions. it's bringing a paradigm shift to healthcare,
powered by increasing availability of healthcare data and rapid progress of
analytics techniques. We survey the present status of AI applications
in healthcare and discuss its future. AI are often applied to
varied sorts of healthcare data (structured and unstructured).
Popular AI techniques include machine learning methods for structured
data, like the classical support vector machine and neural
network, and therefore the modern deep learning, also as tongue processing
for unstructured data. Major disease areas that use AI tools include cancer,
neurology and cardiology. We then review in additional details the AI
applications in stroke, within the three major areas of early
detection and diagnosis, treatment, also as outcome prediction and
prognosis evaluation. We conclude with discussion about pioneer AI
systems, like IBM Watson, and hurdles for real-life deployment of AI.
This is an Open Access article distributed in accordance with the Creative
Commons Attribution Non Commercial (CC BY-NC 4.0) license, which
allows others to distribute, remix, adapt, repose on this work
non-commercially, and license their derivative works on different terms,
provided the first work is correctly cited and
therefore the use is non-commercial.
The term AI in
healthcare is employed to explain the utilization of AI by researchers and
medical practitioners to seek out solutions to existing problems in healthcare
and to supply better healthcare services to patients. Following are some
samples of the utilization of AI in healthcare.
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