This book provides a snapshot of the state of current research at the
interface between machine learning and healthcare with special emphasis
on machine learning projects that are (or are close to) achieving
improvement in patient outcomes. The book provides overviews on a range
of technologies including detecting artefactual events in vital signs
monitoring data; patient physiological monitoring; tracking infectious
disease; predicting antibiotic resistance from genomic data; and
managing chronic disease.
With contributions from an international panel of leading researchers,
this book will find a place on the bookshelves of academic and
industrial researchers and advanced students working in healthcare
technologies, biomedical engineering, and machine learning.