Hands-On Healthcare Data

Errata for Hands-On Healthcare Data

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The errata list is a list of errors and their corrections that were found after the product was released.

The following errata were submitted by our customers and have not yet been approved or disproved by the author or editor. They solely represent the opinion of the customer.

Color Key: Serious technical mistake Minor technical mistake Language or formatting error Typo Question Note Update

Version Location Description Submitted by Date submitted
Printed Page chapter 6 ‘Machine learning and Analytics’
In chapter

Dear Andrew,
I am a PhD student in London, UK, studying the application of graph analytics to routinely collected EPR data (RWD). I have worked for the last 8 years at Great Ormond Street hospital one of the world’s leading paediatric hospitals as a data engineer extracting RWD for research.

I have just finished reading your book ‘Hands-On Healthcare Data’ which I thought was a hugely inciteful and really encapsulated a lot of my experiences over the last 8 years. Huge congratulations and I have recommended the book to all my team!

I have one question. I see graph analytics and the use of graphs for machine learning as two very distinct subjects. When it came to chapter 6 ‘Machine learning and Analytics’ you jump straight to graph embedding and graph neural networks and don’t really touch on the use of graph analysis directly. I was wondering why you made this decision?

A good systematic review is:
Brunson, J.C. and Laubenbacher, R.C., 2018. Applications of network analysis to routinely collected health care data: a systematic review. Journal of the American Medical Informatics Association, 25(2), pp.210-221.

Best wishes,

John Booth
Research Student: MPhil, Faculty of Population Health Sciences, UCL GOS Institute of Child Health
UCL email address:

Data Engineer, Clinical Informatics Research Programme (CIRP)
Great Ormond Street Hospital for Children NHS Foundation Trust
DRIVE Office, 40 Bernard Street, London, WC1N 1ST
GOSH email address:

John Booth  Jan 20, 2023