Increased use of artificial intelligence (AI) is being deployed in
many hospitals and healthcare settings to help improve health care
service delivery. Machine learning (ML) and deep learning (DL)
tools can help guide physicians with tasks such as diagnosis and
detection of diseases and assisting with medical decision making.
This edited book outlines novel applications of AI in e-healthcare.
It includes various real-time/offline applications and case studies
in the field of e-Healthcare, such as image recognition tools for
assisting with tuberculosis diagnosis from x-ray data, ML tools for
cancer disease prediction, and visualisation techniques for
predicting the outbreak and spread of Covid-19. Heterogenous
recurrent convolution neural networks for risk prediction in
electronic healthcare record datasets are also reviewed. Suitable
for an audience of computer scientists and healthcare engineers,
the main objective of this book is to demonstrate effective use of
AI in healthcare by describing and promoting innovative case
studies and finding the scope for improvement across healthcare
services.
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