微卫星不稳定性
荟萃分析
计算机科学
癌症
元数据
人工智能
医学
微卫星
万维网
病理
生物
内科学
生物化学
基因
等位基因
作者
Yiming Ying,Robert J. Ju,Li Wang,Wenkai Li,Yuan Ji,Zhenyu Shi,Jinhan Chen,Mingxian Chen
标识
DOI:10.1016/j.ijmedinf.2024.105685
摘要
Significant challenges persist in the early identification of microsatellite instability (MSI) within current clinical practice. In recent years, with the growing utilization of machine learning (ML) in the diagnosis and management of gastric cancer (GC), numerous researchers have explored the effectiveness of ML methodologies in detecting MSI. Nevertheless, the predictive value of these approaches still lacks comprehensive evidence. Accordingly, this study was carried out to consolidate the accuracy of ML in the prompt detection of MSI in GC.
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