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Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
by
Tang, Zhi-Ri
, Rahaman, Saifur
, Liu, Linjing
, Petinrin, Olutomilayo Olayemi
, Wong, Ka-Chun
, Zhang, Weitong
, Chen, Xingjian
in
Algorithms
/ Biomarkers
/ Biopsy
/ Body fluids
/ Cancer
/ Correlation analysis
/ Datasets
/ Discriminant analysis
/ early cancer detection
/ Feature selection
/ Heterogeneity
/ Hypotheses
/ Learning algorithms
/ liquid biopsy
/ Machine learning
/ Methods
/ Polls & surveys
/ Principal components analysis
/ Review
/ Saliva
/ Standardization
/ Tumors
2021
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Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
by
Tang, Zhi-Ri
, Rahaman, Saifur
, Liu, Linjing
, Petinrin, Olutomilayo Olayemi
, Wong, Ka-Chun
, Zhang, Weitong
, Chen, Xingjian
in
Algorithms
/ Biomarkers
/ Biopsy
/ Body fluids
/ Cancer
/ Correlation analysis
/ Datasets
/ Discriminant analysis
/ early cancer detection
/ Feature selection
/ Heterogeneity
/ Hypotheses
/ Learning algorithms
/ liquid biopsy
/ Machine learning
/ Methods
/ Polls & surveys
/ Principal components analysis
/ Review
/ Saliva
/ Standardization
/ Tumors
2021
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Do you wish to request the book?
Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
by
Tang, Zhi-Ri
, Rahaman, Saifur
, Liu, Linjing
, Petinrin, Olutomilayo Olayemi
, Wong, Ka-Chun
, Zhang, Weitong
, Chen, Xingjian
in
Algorithms
/ Biomarkers
/ Biopsy
/ Body fluids
/ Cancer
/ Correlation analysis
/ Datasets
/ Discriminant analysis
/ early cancer detection
/ Feature selection
/ Heterogeneity
/ Hypotheses
/ Learning algorithms
/ liquid biopsy
/ Machine learning
/ Methods
/ Polls & surveys
/ Principal components analysis
/ Review
/ Saliva
/ Standardization
/ Tumors
2021
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Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
Journal Article
Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
2021
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Overview
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.
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