Type2 diabetes mellitus prediction using data mining algorithms based on the long-noncoding RNAs expression: a comparison of four data mining approaches

Type2 diabetes mellitus prediction using data mining algorithms based on the long-noncoding RNAs expression: a comparison of four data mining approaches

Abstract Background About 90% of patients who have diabetes suffer from Type 2 DM (T2DM). Many studies suggest using the significant role of lncRNAs to improve the diagnosis of T2DM. Machine learning and Data Mining techniques are tools that can improve the analysis and interpretation or extraction...

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Bibliographic Details
Main Authors: Faranak Kazerouni, Azadeh Bayani, Farkhondeh Asadi, Leyla Saeidi, Nasrin Parvizi, Zahra Mansoori
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Bioinformatics
Subjects:
Data mining
Gene expression
Machine learning algorithms
Type 2 diabetes mellitus
Online Access:http://link.springer.com/article/10.1186/s12859-020-03719-8

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http://link.springer.com/article/10.1186/s12859-020-03719-8

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