OncoCatch S Multi-omics early cancer screening

This academic article explores enhancing lung cancer detection by integrating various biological data with machine learning. The researchers investigated using liquid biopsy multi-omics data, specifically analyzing tumor markers, cell-free DNA (cfDNA) concentrations, and copy number variations (CNVs) from blood samples. They found that while individual data types offered some diagnostic power, combining these multi-omics data with machine learning algorithms significantly improved the accuracy in distinguishing lung cancer patients from healthy individuals, particularly in later stages of the disease. The study highlights the potential for developing more precise and non-invasive diagnostic models for lung cancer ...