Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Developing clinical prediction models: a step-by-step guide
238
Zitationen
6
Autoren
2024
Jahr
Abstract
Predicting future outcomes of patients is essential to clinical practice, with many prediction models published each year. Empirical evidence suggests that published studies often have severe methodological limitations, which undermine their usefulness. This article presents a step-by-step guide to help researchers develop and evaluate a clinical prediction model. The guide covers best practices in defining the aim and users, selecting data sources, addressing missing data, exploring alternative modelling options, and assessing model performance. The steps are illustrated using an example from relapsing-remitting multiple sclerosis. Comprehensive R code is also provided.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.294 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.666 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.189 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.588 Zit.
Artificial intelligence in healthcare: past, present and future
2017 · 4.405 Zit.