Heus, Pauline

Prediction models for cardiovascular disease risk in the general population: systematic review

Damen, J. A. A. G., Hooft, L., Schuit, E., Debray, T. P. A., Collins, G. S., Tzoulaki, I., Lassale, C. M., Siontis, G. C. M., Chiocchia, V., Roberts, C., et al. (2016) · BMJ

Health Promotion and Cardiovascular PreventionCardiovascular Health and Risk Factors

Cited by 935

Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis

Damen, J. A., Pajouheshnia, R., Heus, P., Moons, K. G. M., Reitsma, J. B., Scholten, R. J. P. M., Hooft, L., & Debray, T. P. A. (2019) · BMC Medicine

Health Promotion and Cardiovascular PreventionLipoproteins and Cardiovascular Health

Cited by 250

Transparent Reporting of Multivariable Prediction Models in Journal and Conference Abstracts: TRIPOD for Abstracts

Heus, P., Reitsma, J. B., Collins, G. S., Damen, J. A. A. G., Scholten, R. J. P. M., Altman, D. G., Moons, K. G. M., & Hooft, L. (2020) · Annals of Internal Medicine

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 70

Barriers, facilitators and strategies for the implementation of artificial intelligence‐based electrocardiogram interpretation: A mixed‐methods study

Arends, B. K. O., McCormick, J. M., van der Harst, P., Heus, P., & van Es, R. (2025) · European Journal of Clinical Investigation

Artificial Intelligence in Healthcare and EducationHealth Policy Implementation Science

Cited by 5