Analysis of Liver Disorder using Datamining Algorithm

Dr.P.Rajeswari; G.Sophia Reena

Analysis of Liver Disorder using Datamining Algorithm

Dr.P.Rajeswari * §

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G.Sophia Reena

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§ Bharathiyar University

Analysis of Liver Disorder using Datamining Algorithm

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Abstract

There are many disorders of the liver that require clinical care by a physician or other healthcare professional. The study of liver development has significantly contributed to developmental concepts about morphogenesis and differentiation of other organs. Knowledge of the the understanding of human congenital diseases. Significantly, much of understanding of organ development has arisen from analyses of patients with liver deficiencies. In this paper the data classification is based on liver disorder the training data set is developed by collecting data from UCI repository consists of 345 instances with 7 different attributes. The instances in the dataset are pertaining to the two categories of blood tests which are thought to be sensitive to liver disorders that might arise from excessive alcohol consumpt mechanisms that regulate hepatic epithelial cell differentiation has been essential in creating efficient cell culture protocols for programmed differentiation of stem cells to hepatocytes as well as developing cell transplantation therapies. Such knowledge also provides a basis for ion, labeled as Low (L), and (H) to represent the profit as 0 and 1 which result in accuracy and time taken to build the algorithm. WEAK tool is used to classify the data and the data is evaluated using 10-fold cross validation and the results are compared.

References

9 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr.P.Rajeswari, G.Sophia Reena. 1970. "Analysis of Liver Disorder using Datamining Algorithm". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 14).

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GJCST Volume 10 Issue 14

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Submission ReceivedFebruary 11, 2010
Peer Review Double Blind
Handling Editor
Accepted March 4, 2010
Published March 15, 2010

Version of record

v1.2

Issue date

October 14, 2010

Language

English

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Article Matrices

Total Score: 147

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Dr.P.Rajeswari,G.Sophia Reena (PhD/Dr. count: 1)

View Count (all-time): 146

Total Views (Real + Logic): 5482

Total Downloads (simulated): 301

Publish Date: 2010 03, Mon

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Total Views: 5.5K

Total Downloads: 301

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