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.