Openly accessible

Predicting breast cancer risk, recurrence and survivability

Al-Quraishi, Tahsien Ali Hussein 2019, Predicting breast cancer risk, recurrence and survivability, Ph.D. thesis, School of Information Technology, Deakin University.

Attached Files
Name Description MIMEType Size Downloads
alquraishi-predictingbreast-2020.pdf Connect to thesis application/pdf 3.29MB 5

Title Predicting breast cancer risk, recurrence and survivability
Author Al-Quraishi, Tahsien Ali Hussein
Institution Deakin University
School School of Information Technology
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name Ph.D.
Thesis advisor Abawajy, Jemal HusseinORCID iD for Abawajy, Jemal Hussein orcid.org/0000-0001-8962-1222
Chowdhury, Morshed U.ORCID iD for Chowdhury, Morshed U. orcid.org/0000-0002-2866-4955
Date submitted 2019-10
Summary This thesis focuses on predicting breast cancer at early stages by using machine learning algorithms based on biological datasets. The accuracy of those algorithms has been improved to enable the physicians to enhance the success of treatment, thus saving lives and avoiding several further medical tests.
Language eng
Indigenous content off
Description of original 104 p.
Copyright notice ┬ęThe author
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30142351

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 13 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Mon, 21 Sep 2020, 12:00:59 EST by Leanne Swaneveld

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.