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ITI əməkdaşlarının elmi işləri - tezis |
Biblioqrafik təsvir | Jabrayilova , Z.G. Algorithm for early diagnosis of hepatocellular carcinoma based on gene pair similarity / Z.G. Jabrayilova // The international scientific conference “Technology transfer: fundamental principles and innovative technical solutions”. - Tallinn, 2022. - P. 11-13. | Annotasiya | The article proposes an algorithm based on intelligent methods for the early diagnosis of
hepatocellular carcinoma (HCC), known as liver cancer, which is rated third cause of
cancer deaths in the world. Initial diagnosis of HСC is based on laboratory studies,
computer tomography and X-ray examination. However, in some cases, identifying
cancerous tissues as similar non-cancerous tissues (cirrhotic tissues and normal tissues)
made it necessary to perform gene analysis for the diagnosis. To predict HCC based on
such numerous, diverse and heterogeneous unstructured data, preference is given to the
method of artificial intelligence, i.e., machine learning. It shows the possibility of applying
machine learning methods to solve the problem of accurate identification of HCC due to
the compatibility of HCC tissues with identical CwoHCC non-cancerous tissues. The
technology of gene pair profiling using relevant peer databases is described and the
Within-Sample Relative Expression Orderings (REO) technique is used to determine the
gene pair’s similarity. The article also presents a new approach based on The Within-
Sample Relative Expression Orderings technique for determining the gene pair’s
similarity, Incremental feature selection method for feature selection, and Support Vector
Machine methods for gene pair classification. The proposed approach constitutes the
methodological basis of a decision support system for the early diagnosis of HCC, and
the development of such a system may be beneficial for physician decision support in the
relevant field | | Elektron variant | Elektron variant |
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