Clinical Value of Growth Differentiation Factor 15 Detection in the Diagnosis of Early Liver Cancer Based on Data Mining.
The incidence of liver cancer is increasing year by year, and how to effectively diagnose early-stage liver cancer and improve the survival rate of liver cancer patients has become one of the current research topics of concern. Aiming at this problem, it is of great significance for the diagnosis of...
| Publicado en: | BioMed Research International pp. 1 - 12 |
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| Autores principales: | , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/17/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160295795&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160295795 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/17/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 160295795 160295795 160295795 10.1155/2022/4448075 160295795 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Clinical Value of Growth Differentiation Factor 15 Detection in the Diagnosis of Early Liver Cancer Based on Data Mining. aug: au: Guo, Hongyan Liu, Qingfeng affil: Center of Laboratory Test, Beijing YouAn Hospital, Capital Medical University, Beijing, China sug: subj: Liver Neoplasms Diagnosis Early Detection of Cancer Data Mining Cytokines Metabolism Tumor Markers, Biological Metabolism Cytokines Blood Tumor Markers, Biological Blood Human Algorithms Comparative Studies Liver Neoplasms Prognosis Survival Analysis Liver Neoplasms Risk Factors Risk Assessment ab: The incidence of liver cancer is increasing year by year, and how to effectively diagnose early-stage liver cancer and improve the survival rate of liver cancer patients has become one of the current research topics of concern. Aiming at this problem, it is of great significance for the diagnosis of early liver cancer. With the in-depth research on the diagnosis of early-stage liver cancer, the research on growth differentiation factor 15 is gradually carried out, and its performance advantages are of great significance to solve the problem of detection and diagnosis of early-stage liver cancer. This study can improve the accuracy of early diagnosis of liver cancer. The purpose of this paper is to study the application of data mining in the study of clinical value of growth and differentiation factor 15 detection and diagnosis of early liver cancer. In this paper, the data mining algorithm is analyzed, the performance of the algorithm is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results showed that the expression level of GDF-15 was significant in early primary liver cancer (tumor diameter <2.5 cm). Different from normal liver tissue (P < 0.01), there was a significant difference (P < 0.01) compared with adjacent tissue (P < 0.01). Serum GDF-15 can be used as a tumor marker for predicting early stage liver cancer. The high expression of GDF-15 in early stage liver cancer is an independent risk factor affecting the prognosis of liver cancer patients. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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