Big Data in Healthcare

Extracting Knowledge from Point-of-Care Machines
1. Auflage 2017
ISBN: 978-3-319-62988-9
Verlag: Springer

Buch, Englisch, 100 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1766 g

Reihe: SpringerBriefs in Pharmaceutical Science & Drug Development

This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data?

What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.

Zielgruppe

Research

Autoren/Hrsg.

Amirian, Pouria

Lang, Trudie

van Loggerenberg, Francois

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Pharmazie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

Introduction – Improving Healthcare with Big Data.- Data Science and Analytics.- Big Data and Big Data Technologies.- Big Data Analytics for Extracting Disease Surveillance Information: An Untapped Opportunity.- Ebola and Twitter. What Insights Can Public Health Draw from Social Media?

Über Autor(innen)

Pouria Amirian has a PhD in Geospatial Information Science (GIS) and is a Principal Research Scientist in Data Science and Big Data at the Ordnance Survey GB and a Data Science Research Associate with the Global Health Network. He managed and led a joint project (Oxford and Stanford) on “Using Big Data Analysis Tools to Extract Disease Surveillance Information from Point-of-Care Diagnostic Machines”. Pouria has done research and development projects and lectured about Big Data, Data Science, Machine Learning, Spatial Databases, GIS, and Spatial Analytics since 2008.

Trudie Lang is Professor of Global Health Research, Head of the Global Health Network, Senior Research Scientist in Tropical Medicine at Nuffield Department of Medicine, and Research Fellow at Green Templeton College at the University of Oxford. She has a PhD from the London School of Hygiene and Tropical Medicine and has worked within the industry, the World Health Organisation (WHO), NGOs and academia conducting clinical research studies in low-resource settings. Dr Lang is a clinical trial research methodologist with specific expertise in the capacity development and trial operations in low-resource settings. She currently leads the Global Health Network (GHN), which is a focused network of researchers to help clinical researchers with trial design, methods, interpretation of regulations, and general operations.

Francois Van Loggerenberg is Scientific Lead of the Global Health Network, based out of the Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine. Originally trained as a research psychologist, from 2002 to 2012 Francois was employed at the Nelson R Mandela School of Medicine in Durban, South Africa, where he worked initially as the study coordinator on a large HIV pathogenesis study at the Centre for the AIDS Programme of Research in South Africa (CAPRISA). In 2005 he was awarded a Doris Duken Foundation Operations Research For AIDS Care and Treatment In Africa grant that funded his PhD work on enhancing adherence to antiretroviral therapy (2011, London School of Hygiene and Tropical Medicine).