Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)

Plethoric data produced by healthcare transactions are voluminous to be processed and too complex to be analysed by traditional method. The current technology development in data mining is gaining new momentum among health practitioners and researchers for example to improve diagnostic accuracy, ide...

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Main Author:	Zubir, Nazira
Format:	Monograph
Language:	English
Published:	2016
Subjects:	TA165 Engineering instruments, meters, etc. Industrial instrumentation
Online Access:	http://irep.iium.edu.my/52301/ http://irep.iium.edu.my/52301/1/HTM_RADIOLOGY_CENTRE_DATAMINING_NAZIRA_230516_edit.docx

id	iium-52301
recordtype	eprints
spelling	iium-523012018-05-05T16:35:54Z http://irep.iium.edu.my/52301/ Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique) Zubir, Nazira TA165 Engineering instruments, meters, etc. Industrial instrumentation Plethoric data produced by healthcare transactions are voluminous to be processed and too complex to be analysed by traditional method. The current technology development in data mining is gaining new momentum among health practitioners and researchers for example to improve diagnostic accuracy, identifying high risk patients and tracking concepts from unstructured data. In setting up a new Radiology Centre, the data mining technology specifically image mining is addressed. Data mining is the process of mining the hidden patterns from the huge data. Data mining scans a huge volume of data to find out the patterns and correlations among the patterns. Data mining requires the use of data analysis tool containing statistical model, mathematical algorithms and machine learning methods to determine previously unknown, valid patterns and relationships in huge volume data. The latest development of data mining in the field of biomedical imaging integrates the fuzzy logic, neural network and expert system. This development is very promising indeed as to provide the efficient and precise diagnosing platform for the cancer patients or patients who suffer from other diseases. The outline of how the systems could be integrated in the image mining for instance in diagnosing lung cancer is discussed. The examples of image processing and classification techniques used for predicting lung cancer are summarized. The similar techniques can be adopted to diagnose other types of cancer for examples breast and brain cancers. Keywords: healthcare management, data mining, fuzzy logic, neural network, expert system, biomedical imaging 2016-05-24 Monograph NonPeerReviewed application/pdf en http://irep.iium.edu.my/52301/1/HTM_RADIOLOGY_CENTRE_DATAMINING_NAZIRA_230516_edit.docx Zubir, Nazira (2016) Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique). Other. UNSPECIFIED. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA165 Engineering instruments, meters, etc. Industrial instrumentation
spellingShingle	TA165 Engineering instruments, meters, etc. Industrial instrumentation Zubir, Nazira Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
description	Plethoric data produced by healthcare transactions are voluminous to be processed and too complex to be analysed by traditional method. The current technology development in data mining is gaining new momentum among health practitioners and researchers for example to improve diagnostic accuracy, identifying high risk patients and tracking concepts from unstructured data. In setting up a new Radiology Centre, the data mining technology specifically image mining is addressed. Data mining is the process of mining the hidden patterns from the huge data. Data mining scans a huge volume of data to find out the patterns and correlations among the patterns. Data mining requires the use of data analysis tool containing statistical model, mathematical algorithms and machine learning methods to determine previously unknown, valid patterns and relationships in huge volume data. The latest development of data mining in the field of biomedical imaging integrates the fuzzy logic, neural network and expert system. This development is very promising indeed as to provide the efficient and precise diagnosing platform for the cancer patients or patients who suffer from other diseases. The outline of how the systems could be integrated in the image mining for instance in diagnosing lung cancer is discussed. The examples of image processing and classification techniques used for predicting lung cancer are summarized. The similar techniques can be adopted to diagnose other types of cancer for examples breast and brain cancers. Keywords: healthcare management, data mining, fuzzy logic, neural network, expert system, biomedical imaging
format	Monograph
author	Zubir, Nazira
author_facet	Zubir, Nazira
author_sort	Zubir, Nazira
title	Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
title_short	Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
title_full	Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
title_fullStr	Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
title_full_unstemmed	Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
title_sort	setting up a new radiology center technology for improvement : data mining (image mining technique)
publishDate	2016
url	http://irep.iium.edu.my/52301/ http://irep.iium.edu.my/52301/1/HTM_RADIOLOGY_CENTRE_DATAMINING_NAZIRA_230516_edit.docx
first_indexed	2023-09-18T21:14:07Z
last_indexed	2023-09-18T21:14:07Z
_version_	1777411447489298432

Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)

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