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Diagnostic Classification of Cancer Using DNA Microarrays and Artificial Intelligence
Author(s) -
GREER BRADEN T.,
KHAN JAVED
Publication year - 2004
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1310.007
Subject(s) - variety (cybernetics) , computer science , dna microarray , artificial intelligence , cancer , machine learning , bioinformatics , data science , medicine , gene , biology , gene expression , biochemistry
A bstract : The application of artificial intelligence (AI) to microarray data has been receiving much attention in recent years because of the possibility of automated diagnosis in the near future. Studies have been published predicting tumor type, estrogen receptor status, and prognosis using a variety of AI algorithms. The performance of intelligent computing decisions based on gene expression signatures is in some cases comparable to or better than the current clinical decision schemas. The goal of these tools is not to make clinicians obsolete, but rather to give clinicians one more tool in their armamentarium to accurately diagnose and hence better treat cancer patients. Several such applications are summarized in this chapter, and some of the common pitfalls are noted.