Machine Learning-Assisted Evaluation of Circulating DNA Quantitative Analysis for Cancer Screening.

ABSTRACT: While the utility of circulating cell-free DNA (cfDNA) in cancer screening and early detection have recently been investigated by testing genetic and epigenetic alterations, here, an original approach by examining cfDNA quantitative and structural features is developed. First, the potential of cfDNA quantitative and structural parameters is independently demonstrated in cell culture, murine, and human plasma models. Subsequently, these variables are evaluated in a large retrospective cohort of 289 healthy individuals and 983 patients with various cancer types; after age resampling, this evaluation is done independently and the variables are combined using a machine learning approach. Implementation of a decision tree prediction model for the detection and classification of healthy and canc

SUBMITTER: Tanos R 

PROVIDER: S-EPMC7509651 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature