NDLI: Spatial data mining using association rules and fuzzy logic for autonomous exploration of geo-referenced cancer data in Western Tamilnadu, India

Content Provider	Springer Nature Link
Author	Selvaraj, Janani Somanathan, Balasubramanian Parasur Babu, Harathi Ramachandran, Sridhar Marimuthu, Prashanthi Devi
Copyright Year	2015
Abstract	Data mining using association rule is widely applied in medicine, particularly in cancer epidemiology. It is reported that this technique has certain uncertainty. To minimize the uncertainty, fuzzy logic is used with association rules. To demonstrate the efficiency of these methods further, geographical information system tool is used to spatially view results obtained from above-mentioned techniques. For the present study, cancer data were taken due its disparity among different populations/locations and also because it is a serious concern that affects our socio-economic well being. Cancer is a family of diseases arising due to varied factors and there is no one cause and cure until the definite causative factor is determined. Data mining approach using association rule technique was applied to extract association between diet and incidences of cancer and was interpreted using fuzzy logic. The spatial data were displayed through map objects, and apriori algorithm is used to evaluate, visualize, and analyze the results from the data mining process. In this regard, data consisting of 3000 cancer cases were scrutinized which involves 16 parameters, 160 types of cancer, and 5 types of dietary habits including smoking, mixed diet, alcohol, betel nut, and tobacco chewing. Association rule mining reduces 800 combinations of cancer and habits to 129 cancer types and 3 habits and plots the respective location in the map through map objects. Fuzzy logic is used to find the spatio-habits linked. Association rule integrated with fuzzy logic reveals the influence of diet on cancer and its spatial pattern of the disease distribution. This technique enables us to provide the interpretation for the severity of disease that needs further attention and decision making.
Starting Page	1
Ending Page	11
Page Count	11
File Format	PDF
ISSN	21926662
Journal	Network Modeling Analysis in Health Informatics and Bioinformatics
Volume Number	4
Issue Number	1
e-ISSN	21926670
Language	English
Publisher	Springer Vienna
Publisher Date	2015-08-12
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fuzzy logic GIS Computational Biology/Bioinformatics Association rule Apriori algorithm Complex Networks Health Informatics Bioinformatics Cancer
Content Type	Text
Resource Type	Article
Subject	Urology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Significant patterns for oral cancer detection: association rule on clinical examination and history data

Mining Spatial Association Rules in Census Data (2002)

Data mining techniques for autonomous exploration of large volumes of geo-referenced crime data (2001)

Data mining techniques for autonomous exploration of large volumes of geo-referenced crime data (2001)

COLLABORATIVE WEB RECOMMENDATION SYSTEMS BASED ON AN EFFECTIVE FUZZY ASSOCIATION RULE MINING ALGORITHM (FARM)

Mining fuzzy amino acid associations in peptide sequences of mycobacterium tuberculosis complex (MTBC)

Mining and filtering multilevel spatial association rules with ARES (2005)

Mining and filtering multi-level spatial association rules with ares (2005)

A Fast Fuzzy Association Rules Mining Algorithm Utilizing Output Field Specification(COMPUTATIONAL INTELLIGENCE)

Spatial data mining using association rules and fuzzy logic for autonomous exploration of geo-referenced cancer data in Western Tamilnadu, India

Similar Documents

Significant patterns for oral cancer detection: association rule on clinical examination and history data

Mining Spatial Association Rules in Census Data (2002)

Data mining techniques for autonomous exploration of large volumes of geo-referenced crime data (2001)

Data mining techniques for autonomous exploration of large volumes of geo-referenced crime data (2001)

COLLABORATIVE WEB RECOMMENDATION SYSTEMS BASED ON AN EFFECTIVE FUZZY ASSOCIATION RULE MINING ALGORITHM (FARM)

Mining fuzzy amino acid associations in peptide sequences of mycobacterium tuberculosis complex (MTBC)

Mining and filtering multilevel spatial association rules with ARES (2005)

Mining and filtering multi-level spatial association rules with ares (2005)

A Fast Fuzzy Association Rules Mining Algorithm Utilizing Output Field Specification(COMPUTATIONAL INTELLIGENCE)

Spatial data mining using association rules and fuzzy logic for autonomous exploration of geo-referenced cancer data in Western Tamilnadu, India