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Books > Medicine > Clinical & internal medicine > Medical diagnosis
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Disruptive Trends in Computer Aided Diagnosis (Hardcover)
Loot Price: R3,836
Discovery Miles 38 360
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Disruptive Trends in Computer Aided Diagnosis (Hardcover)
Series: Chapman & Hall/CRC Computational Intelligence and Its Applications
Expected to ship within 12 - 19 working days
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Disruptive Trends in Computer Aided Diagnosis collates novel
techniques and methodologies in the domain of content based image
classification and deep learning/machine learning techniques to
design efficient computer aided diagnosis architecture. It is aimed
to highlight new challenges and probable solutions in the domain of
computer aided diagnosis to leverage balancing of sustainable
ecology. The volume focuses on designing efficient algorithms for
proposing CAD systems to mitigate the challenges of critical
illnesses at an early stage. State-of-the-art novel methods are
explored for envisaging automated diagnosis systems thereby
overriding the limitations due to lack of training data, sample
annotation, region of interest identification, proper segmentation
and so on. The assorted techniques addresses the challenges
encountered in existing systems thereby facilitating accurate
patient healthcare and diagnosis. Features: An integrated
interdisciplinary approach to address complex computer aided
diagnosis problems and limitations. Elucidates a rich summary of
the state-of-the-art tools and techniques related to automated
detection and diagnosis of life threatening diseases including
pandemics. Machine learning and deep learning methodologies on
evolving accurate and precise early detection and medical diagnosis
systems. Information presented in an accessible way for students,
researchers and medical practitioners. The volume would come to the
benefit of both post-graduate students and aspiring researchers in
the field of medical informatics, computer science and electronics
and communication engineering. In addition, the volume is also
intended to serve as a guiding factor for the medical practitioners
and radiologists in accurate diagnosis of diseases.
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