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Vehicle Detection Using Alex Net and Faster R-CNN Deep Learning Models: A Comparative Study Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Bridging the Gap in Personalised Medicine Through Data Driven Genomics

Authors : Ummul Hanan Mohamad, Mohamad Taha Ijab, Rabiah Abdul Kadir

Published in: Advances in Visual Informatics

Publisher: Springer International Publishing

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Abstract

Personalised medicine has been visualised as the ultimate healthcare practise, as the treatment will be customised to the patient’s need. This will eliminate the “one-for-all” approach, thus reducing the potential drug’s side effects, ineffective drug doses and severe complications due to unsuitable drugs prescribed. As the cost for genomics sequencing started to plummet, this condition has driven extensive studies on many disease genomics, generating genomics big data. However, without an in-depth analysis and management of the data, it will be difficult to reveal and relate the link between the genomics with the diseases in order to accomplish personalised medicine. The main reason behind this is that genomics data has never been straightforward and is poorly understood. Therefore, this paper purposely discusses how the advances in technology have aid the understanding of genomics big data, thus a proposed framework is highlighted to help change the landscape of personalised medicine.

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previous chapter Towards Big Data Quality Framework for Malaysia’s Public Sector Open Data Initiative
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Metadata
Title
Bridging the Gap in Personalised Medicine Through Data Driven Genomics
Authors
Ummul Hanan Mohamad
Mohamad Taha Ijab
Rabiah Abdul Kadir
Copyright Year
2017
Book
Advances in Visual Informatics

Print ISBN: 978-3-319-70009-0

Electronic ISBN: 978-3-319-70010-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-70010-6_9

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