Early Cancer Detection from Multianalyte Blood Test Results
Publication in refereed journal

香港中文大學研究人員
替代計量分析
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其它資訊
摘要The early detection of cancers has the potential to save many lives. A recent attempt has been demonstrated successful. However, we note several critical limitations. Given the central importance and broad impact of early cancer detection, we aspire to address those limitations. We explore different supervised learning approaches for multiple cancer type detection and observe significant improvements; for instance, one of our approaches (i.e., CancerA1DE) can double the existing sensitivity from 38% to 77% for the earliest cancer detection (i.e., Stage I) at the 99% specificity level. For Stage II, it can even reach up to about 90% across multiple cancer types. In addition, CancerA1DE can also double the existing sensitivity from 30% to 70% for detecting breast cancers at the 99% specificity level. Data and model analysis are conducted to reveal the underlying reasons.
著者Ka-Chun Wong, Junyi Chen, JiaoZhang, Jiecong Lin, Shankai Yan, Shxiong Zhang, Xiangtao Li, Cheng Liang, Chengbin Peng, Qiuzhen Lin, Sam Kwong, JunYu
期刊名稱iScience
出版年份2019
月份5
日期31
卷號15
出版社Elsevier (Cell Press): OAJ / Elsevier
頁次332
國際標準期刊號2589-0042
語言美式英語

上次更新時間 2020-13-08 於 04:40