Composite biomarker algorithms integrate multiple indicators to enhance diagnostic accuracy and patient stratification. They reduce uncertainty by combining signals from diverse sources, offering robust, reproducible results for complex diseases.
By leveraging machine learning and statistical fusion, these algorithms guide tailored treatments and improve outcomes in real-world clinical settings.