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- W4285178045 abstract "Recently, cancer has become one of the causes of death. It is necessary to actively seek the most effective solutions for the treatment and diagnosis of cancer. Recently, rapidly enhance the computing power and their progress in field of artificial intelligence (AI), especially in the field of deep learning (DL). DL has been used in many area of medicine, including image, diagnostics, digital pathology, hospital prediction, drug development, cancer and supportive cell classification, and physician support. In this research paper, we study the most novel deep learning approach and classification of cancer-based tumor RNA sequence (RNA-Seq) gene expression data. However, there are many problems for the treatment of cancer and tumors of genetic causes that cause changes or disorders. RNA sequencing and profiling of gene expression in the body at the molecular level are an effective method for modeling information about cancer diagnosis. Data on gene expression has been used to build classification models that support cancer treatment. The cancer feature extraction and classification will be investigated in this research. The paper also explores the latest research on the application of deep learning and machine learning to tumor gene expression data." @default.
- W4285178045 created "2022-07-14" @default.
- W4285178045 creator A5004909044 @default.
- W4285178045 date "2022-01-01" @default.
- W4285178045 modified "2023-09-26" @default.
- W4285178045 title "A Novel Classification of Cancer Based on Tumor RNA-Sequence (RNA-Seq) Gene Expression" @default.
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- W4285178045 doi "https://doi.org/10.1007/978-981-16-9650-3_43" @default.
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