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Data mining technique for medical informatics: detecting gastric cancer using case‐based reasoning and single nucleotide polymorphisms
Author(s) -
Chun SeChul,
Kim Jin,
Hahm KiBaik,
Park YoonJoo,
Chun SeHak
Publication year - 2008
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2008.00446.x
Subject(s) - computer science , informatics , data mining , translational bioinformatics , categorical variable , knowledge extraction , snp , human genome , single nucleotide polymorphism , artificial intelligence , data science , machine learning , genomics , gene , biology , genome , genotype , electrical engineering , engineering , biochemistry
Although data mining and knowledge discovery techniques have recently been used to diagnose human disease, little research has been conducted on disease diagnostic modelling using human gene information. Furthermore, to our knowledge, no study has reported on diagnosis models using single nucleotide polymorphism (SNP) information. A disease diagnosis model using data mining techniques and SNP information should prove promising from a practical perspective as more information on human genes becomes available. Data mining and knowledge discovery techniques can be put to practical use detecting human disease, since a haplotype analysis using high‐density SNP markers has gained great attention for evaluating human genes related to various human diseases. This paper explores how data mining and knowledge discovery can be applied to medical informatics using human gene information. As an example, we applied case‐based reasoning to a cancer detection problem using human gene information and SNP analysis because case‐based reasoning has been applied in medicine relatively less often than other data mining techniques. We propose a modified case‐based reasoning method that is appropriate for associated categorical variables to use in detecting gastric cancer.