Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence–Driven Clinical Prediction Model: Protocol from the Coronary Artery Disease Risk Estimation and Early Detection Consortium

Rutger van Mierlo   ^{1, 2, 3 *} , MSc, MD ;   Bart Scheenstra   ^{4 *} , BSc, MSc, MD ;   Joost Verbeek   ⁵ , BSc, MSc, PhD ;   Anke Bruninx   ² , BSc, MSc ;   Petros Kalendralis   ² , BSc, MSc, PhD ;   Inigo Bermejo   ² , BSc, MSc, PhD, Prof Dr ;   Andre Dekker   ² , BSc, MSc, IR, PhD, Prof Dr ;   Arnoud van 't Hof   ^{1, 3, 6} , BSc, MSc, MD, PhD, Prof Dr Med ;   Marieke Spreeuwenberg   ⁵ , BSc, MSc, PhD, Prof Dr ;   Laura Hochstenbach   ⁵ , BSc, MSc, PhD

¹ Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands

² Department of Radiation Oncology (Maastro), Research Institute for Oncology and Reproduction (GROW), Maastricht University, Maastricht, The Netherlands

³ Department of Cardiology, Zuyderland Medisch Centrum, Heerlen, The Netherlands

⁴ Department of Cardiothoracic Surgery, Heart and Vascular Center, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands

⁵ Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands

⁶ Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands

*these authors contributed equally