Cardiovascular risk assessment enhanced by automated machine learning in a multi-phase study
Abstract
Abstract Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction by processing large datasets and developing tailored models without the need for extensive data science expertise. Using clinical datasets from the LURIC ( n = 3316) and UMC/M ( n = 423) studies, we built AutoML models to predict Lp(a), specific CVDs and CVD-related mortality in three phases. Phase 1 identified key CVD determinants such as age, Lp(a), troponin T, BMI and cholesterol with good accuracy (AUC 0.6249 to 0.9101). Phase 2 validated models in the UMC/M dataset and showed robust performance (AUC 0.7224 to 0.8417), with SHAP analysis highlighting predictors like statin therapy, age and NTproBNP. Phase 3 focused on cardiovascular mortality prediction, achieving high AUC values (0.74 to 0.85) and showed data drift, highlighting the need for model adjustment.
Article Details
Authors (10)
Igor Bibi
Daniel Schaffert
Philipp Blanke
From Gagnon Cardiovascular Institute, Morristown Medical Center, Morristown, NJ (P.G.); Columbia University Medical Center/New York Presbyterian Hospital (A.S., R.T.H., M.B.L.), the Cardiovascular Research Foundation (D.J.C., R.T.H., B.R., M.B.L.), and Weill Cornell Medicine (B.R.), New York, and St. Francis Hospital and Heart Center, Roslyn (D.J.C.) — all in New York; University of Colorado Health, Medical Center of the Rockies, Loveland (J.B.O.); Laval University, Quebec, QC (P.P.), St. Paul’s Hospital, University of British Columbia, Vancouver (P.B., J.L.), and McMaster University, Hamilton, ON (T.S.) — all in Canada; Vanderbilt University Medical Center, Nashville (B.R.L., K.G.); Emory University, Atlanta (V.B.); the Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Stanford University, Stanford (W.F.F.), VA Palo Alto Health Care System, Palo Alto (W.F.F.), California Pacific Medical Center, San Francisco (D.V.D.), Cedars–Sinai Medical Center, Los Angeles (R.R.M.), and Edwards ...
Lorenz Illian
Federico Lenzing
Niklas Martin
Jan Leipe
Winfried März
Ksenija Stach
Victor Olsavszky