Tag: machine learning

Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis

This 2017 study utilized data from 6,814 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) to evaluate the effectiveness of machine learning, specifically random survival forests, in predicting six cardiovascular outcomes over a 12-year follow-up. Incorporating 735 variables from imaging, biomarker panels, ECG, and questionnaires, the machine learning models outperformed

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Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set

This clinical validation study evaluated a blood-based multi-cancer early detection (MCED) test that analyzes cell-free DNA (cfDNA) methylation patterns using targeted sequencing and machine learning. Conducted as part of the CCGA study, the analysis included 4,077 participants (2,823 with cancer, 1,254 without). The test achieved a specificity of 99.5% and

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