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Copy number variation in plasma as a tool for lung cancer prediction using Extreme Gradient Boosting (XGBoost) classifier

https://doi.org/10.1111/1759-7714.13204
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Annual Report to the Nation on the Status of Cancer, part I: National cancer statistics
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An intelligent system for automated breast cancer diagnosis and prognosis using SVM based classifiers
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Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network
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Machine learning applications in cancer prognosis and prediction
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Risk factors of Lung Cancer in nonsmoker
inferredcites →https://doi.org/10.1016/j.gde.2016.12.003openalex-snapshot
Circulating-tumor DNA as an early detection and diagnostic tool
inferredcites →https://doi.org/10.1016/j.lungcan.2015.07.002openalex-snapshot
Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls
inferredcites →https://doi.org/10.1016/j.lungcan.2018.04.008openalex-snapshot
Genomic alterations of plasma cell-free DNAs in small cell lung cancer and their clinical relevance
inferredcites →https://doi.org/10.1016/j.procs.2016.04.224openalex-snapshot
Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis
inferredcites →https://doi.org/10.1016/s0140-6736(16)30958-8openalex-snapshot
Lung cancer: current therapies and new targeted treatments
inferredcites →https://doi.org/10.1038/bjc.1997.13openalex-snapshot
Small-cell lung cancer is characterized by a high incidence of deletions on chromosomes 3p, 4q, 5q, 10q, 13q and 17p
inferredcites →https://doi.org/10.1038/nature08822openalex-snapshot
The landscape of somatic copy-number alteration across human cancers
inferredcites →https://doi.org/10.1038/nbt.2897openalex-snapshot
Tumor signatures in the blood
inferredcites →https://doi.org/10.1038/nrclinonc.2017.198openalex-snapshot
Determinants and clinical implications of chromosomal instability in cancer
inferredcites →https://doi.org/10.1038/s41422-018-0014-xopenalex-snapshot
Circulating tumor DNA 5-hydroxymethylcytosine as a novel diagnostic biomarker for esophageal cancer
inferredcites →https://doi.org/10.1038/s41586-019-1272-6openalex-snapshot
Genome-wide cell-free DNA fragmentation in patients with cancer
inferredcites →https://doi.org/10.1038/s41598-018-19907-9openalex-snapshot
Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network
inferredcites →https://doi.org/10.1038/sj.onc.1205836openalex-snapshot
Chromosomal imbalances in human lung cancer
inferredcites →https://doi.org/10.1073/pnas.1320659110openalex-snapshot
Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients
inferredcites →https://doi.org/10.1073/pnas.1500076112openalex-snapshot
Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients
inferredcites →https://doi.org/10.1093/annonc/mdw619openalex-snapshot
Circulating tumor markers: harmonizing the yin and yang of CTCs and ctDNA for precision medicine
inferredcites →https://doi.org/10.1109/jbhi.2016.2636448openalex-snapshot
Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence
inferredcites →https://doi.org/10.1126/scitranslmed.3004742openalex-snapshot
Detection of Chromosomal Alterations in the Circulation of Cancer Patients with Whole-Genome Sequencing
inferredcites →https://doi.org/10.1136/thoraxjnl-2013-204681openalex-snapshot
DNA copy number changes as diagnostic tools for lung cancer
inferredcites →https://doi.org/10.1145/2939672.2939785openalex-snapshot
XGBoost
inferredcites →https://doi.org/10.1158/1078-0432.ccr-16-2497openalex-snapshot
Utility of Genomic Assessment of Blood-Derived Circulating Tumor DNA (ctDNA) in Patients with Advanced Lung Adenocarcinoma
inferredcites →https://doi.org/10.1177/117693510600200030openalex-snapshot
Applications of Machine Learning in Cancer Prediction and Prognosis
inferredcites →https://doi.org/10.1186/1471-2105-10-80openalex-snapshot
CNV-seq, a new method to detect copy number variation using high-throughput sequencing
inferredcites →https://doi.org/10.1186/gb-2011-12-4-r41openalex-snapshot
GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
inferredcites →https://doi.org/10.1186/gm62openalex-snapshot
Copy number variations and cancer
inferredcites →https://doi.org/10.1200/jco.2006.24.18_suppl.7082openalex-snapshot
Temporal trends in small cell lung cancer: Analysis of the national Surveillance, Epidemiology, and End-Results (SEER) database
inferredcites →https://doi.org/10.1272/jnms.66.107openalex-snapshot
Chromosome 8 copy numbers and the c-myc gene amplification in non-small cell lung cancer. Analysis by interphase cytogenetics.
inferredcites →https://doi.org/10.3322/caac.21338openalex-snapshot
Cancer statistics in China, 2015
inferredcites →https://doi.org/10.4065/83.5.584openalex-snapshot
Non-Small Cell Lung Cancer: Epidemiology, Risk Factors, Treatment, and Survivorship
inferredcites →https://doi.org/10.4230/oasics.dx.2024.27openalex-snapshot
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
inferredcites →https://doi.org/10.7150/jca.10747openalex-snapshot
Non-invasive Analysis of Genomic Copy Number Variation in Patients with Hepatocellular Carcinoma by Next Generation DNA Sequencing

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