Background Accurately predicting the survival rate of breast cancer patients is a major issue
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …

A risk prediction model is a mathematical equation that uses patient risk factor data to
estimate the probability of a patient experiencing a healthcare outcome. Risk prediction …

Background Clinical prediction models should be validated before implementation in clinical
practice. But is favorable performance at internal validation or one external validation …

Zachęca się pracowników opieki zdrowotnej, aby w pełni uwzględniali te wytyczne
ESC/EACTS, gdy dokonują oceny klinicznej, a także kiedy określają i realizują medyczne …

Objective Predictive analytics create opportunities to incorporate personalized risk estimates
into clinical decision support. Models must be well calibrated to support decision-making, yet …

Clinical prediction models (CPMs) have become fundamental for risk stratification across
healthcare. The CPM pipeline (development, validation, deployment, and impact …

Clinical prediction models must be appropriately validated before they can be used. While
validation studies are sometimes carefully designed to match an intended population/setting …

Surgical treatment for angina pectoris was first proposed in 1899. Decades of experimental
surgery for coronary artery disease finally led to the introduction of coronary artery bypass …

Abstract Model calibration, critical to the success and safety of clinical prediction models,
deteriorates over time in response to the dynamic nature of clinical environments. To support …

Objective Clinical prediction models require updating as performance deteriorates over time.
We developed a testing procedure to select updating methods that minimizes overfitting …