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Health Informatics: A Computational Perspective in Healthcare (Hardcover, 1st ed. 2021)
Loot Price: R5,240
Discovery Miles 52 400
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Health Informatics: A Computational Perspective in Healthcare (Hardcover, 1st ed. 2021)
Series: Studies in Computational Intelligence, 932
Expected to ship within 12 - 17 working days
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This book presents innovative research works to demonstrate the
potential and the advancements of computing approaches to utilize
healthcare centric and medical datasets in solving complex
healthcare problems. Computing technique is one of the key
technologies that are being currently used to perform medical
diagnostics in the healthcare domain, thanks to the abundance of
medical data being generated and collected. Nowadays, medical data
is available in many different forms like MRI images, CT scan
images, EHR data, test reports, histopathological data and doctor
patient conversation data. This opens up huge opportunities for the
application of computing techniques, to derive data-driven models
that can be of very high utility, in terms of providing effective
treatment to patients. Moreover, machine learning algorithms can
uncover hidden patterns and relationships present in medical
datasets, which are too complex to uncover, if a data-driven
approach is not taken. With the help of computing systems, today,
it is possible for researchers to predict an accurate medical
diagnosis for new patients, using models built from previous
patient data. Apart from automatic diagnostic tasks, computing
techniques have also been applied in the process of drug discovery,
by which a lot of time and money can be saved. Utilization of
genomic data using various computing techniques is another emerging
area, which may in fact be the key to fulfilling the dream of
personalized medications. Medical prognostics is another area in
which machine learning has shown great promise recently, where
automatic prognostic models are being built that can predict the
progress of the disease, as well as can suggest the potential
treatment paths to get ahead of the disease progression.
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