Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

被引:28
作者
Liu, Linjing [1 ]
Chen, Xingjian [1 ]
Petinrin, Olutomilayo Olayemi [1 ]
Zhang, Weitong [1 ]
Rahaman, Saifur [1 ]
Tang, Zhi-Ri [1 ]
Wong, Ka-Chun [1 ,2 ]
机构
[1] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Hong Kong Inst Data Sci, Hong Kong, Peoples R China
来源
LIFE-BASEL | 2021年 / 11卷 / 07期
基金
中国国家自然科学基金;
关键词
machine learning; early cancer detection; liquid biopsy; CIRCULATING TUMOR-CELLS; REJECTIVE MULTIPLE TEST; FREE DNA; LUNG-CANCER; FEATURE-SELECTION; CROSS-VALIDATION; STATISTICAL COMPARISONS; PERIPHERAL-BLOOD; DATA SETS; PLASMA;
D O I
10.3390/life11070638
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.
引用
收藏
页数:39
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