LASSO Regression

How it works

Benefits

Dosage & preparation

Comparisons

Evidence quality

Highlighted claims

• LASSO regression was used as a supervised regularisation method that incorporated cancer diagnosis as the outcome. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods
• LASSO was applied to the full 5,821-patient cohort using multiply imputed data. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods
• The LASSO model treated biomarkers as continuous variables to preserve information and stabilize coefficient estimation. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods
• Variables with non-zero LASSO coefficients were included in the LASSO score, with points assigned by coefficient magnitude. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods
• LASSO's higher specificity may reduce unnecessary investigations but could miss more cancers than LCA. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods
• The LASSO score was likely most attuned to late-stage malignancy because it selected ALP as a high-weight marker in a cohort with many metastatic and late-stage cancers. — Exploring a panel of serum biomarkers for cancer risk in patients with non-specific symptoms: a comparative analysis of feature selection methods