Metabolic Phenotyping in Personalized and Public Healthcare provides information on the widespread recognition that a personalized or stratified approach to patient treatment may offer a more efficient and effective healthcare solution than phenotype-led approaches.In order to achieve that objective, a deep personal description is required at the level of the genome, proteome, metabolome, or preferably a combination of these aided by technology. This book, edited and written by the outstanding luminaries of this evolving field, evaluates metabolic profiling and its uses across personalized and population healthcare, while also covering the advent of new technology fields, such as surgical metabonomics. In addition, the text presents specific examples of where this technology has been used clinically and with efficacy, pointing towards a framework and protocol for usage as it hits the clinical mainstream. – Translates the conjunction of new surgical tools for intraoperative, real-time, metabolite evaluation and direct analysis of biofluid samples into novel options for augmented clinical decision-making- Discusses longitudinal sampling from individual patients for stratified medicine- Covers high resolution analytical spectroscopy and sophisticated computational modelling for prediction of adverse reactions in critical care scenarios, prognostic evaluation of cancer from biofluidism, and prognostic prediction of metabolism or response of patients to pharmaceutical interventions- Encapsulates recent technology options for broader population profiling considerations, in particular, the metabolome-wide association studies (MWAS) that aid the translational researcher in identifying metabolic patterns associated with disease- Foreword written by Professor Dame Sally Davies who is the Chief Medical Officer for England
Ara Darzi & Elaine Holmes
Metabolic Phenotyping in Personalized and Public Healthcare [EPUB ebook]
Metabolic Phenotyping in Personalized and Public Healthcare [EPUB ebook]
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Language English ● Format EPUB ● ISBN 9780128004142 ● Editor Ara Darzi & Elaine Holmes ● Publisher Elsevier Science ● Published 2016 ● Downloadable 3 times ● Currency EUR ● ID 4853553 ● Copy protection Adobe DRM
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