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  • 标题:Data mining visualization to support biochemical markers for liver fibrosis in patients with chronic hepatitis C virus
  • 本地全文:下载
  • 作者:Associate Professor Ayman Khedr ; Mr. Samir Sabry
  • 期刊名称:International Journal of Artificial Intelligence and Expert Systems (IJAE)
  • 电子版ISSN:2180-124X
  • 出版年度:2011
  • 卷号:2
  • 期号:3
  • 页码:107-116
  • 出版社:Computer Science Journals
  • 摘要:The reference diagnostic test to detect fibrosis is liver biopsy (LB), a procedure subject to various limitations, including risk of patient injury and sampling error. FibroTest (FT) and ActiTest (AT) are biochemical markers (noninvasive tests) used in determining the level of fibrosis and the degree of necroinflammatory activity in the liver. The objective of this work is to discover the differences in the temporal patterns between noninvasive tests and liver biopsy by visualization tools, which made it easier to understand the relations of the complicated rules. This Study ware focused on the major serum fibrosis markers (FT/AT). The test uses a combination of serum biochemical markers with visualization technique to evaluate whether biochemical markers can be used to estimate the stage of liver fibrosis and necro-inflammatory activity in the liver.
  • 关键词:Data Mining; Visualization; Hepatitis C; Serum Markers; Liver Fibrosis
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