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A serum exosomal microRNA-based artificial intelligence diagnostic model for highly accurate detection of hepatocellular carcinoma
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作者 Jin-Seong Hwang sugi lee +19 位作者 Gyeonghwa Kim Hoibin Jeong Kiyoon Kwon Eunsun Jung Yuna Roh Taesang Son Hana lee Moo-Seung lee Kyoung-Jin Oh HyeWon lee Yu Rim lee Soo Young Park Won Young Tak Hyun Seung Ban Hyun-Soo Cho Mi-Young Son Jang-Seong Kim Keun Hur Dae-Soo Kim Tae-Su Han 《Cancer Communications》 2025年第9期1188-1193,共6页
Hepatocellular carcinoma(HCC)is a critical cancerworldwide due to its low survival rate[1].In the United States,the overall 5-year survival rate of patients with HCC is 22%,which decreases sharply with cancer progress... Hepatocellular carcinoma(HCC)is a critical cancerworldwide due to its low survival rate[1].In the United States,the overall 5-year survival rate of patients with HCC is 22%,which decreases sharply with cancer progression[2].Early detection of HCC improves patient survival.Serum alpha-fetoprotein(AFP)is a widely used biomarker for the diagnosis of HCC,but it is often elevated in patients with cirrhosis,resulting in false-positive results[3].Diagnostic markers for early detection of HCC have been investigated previously[4],but none are widely applied in clinical settings. 展开更多
关键词 survival rate exosomal hepatocellular carcinoma MICRORNA early detection artificial intelligence diagnostic model SERUM
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