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This study develops and validates a multivariable prediction model to rank order adult heart transplant candidates by medical urgency.
Review highlights the potential of AI models in predicting cardiovascular disease risks but emphasizes the need for independent external validation to ensure their clinical applicability.
An external validation study evaluates the performance of a prediction model in new data, but many of these studies are too small to provide reliable answers. In the third article of their series on model evaluation, Riley and colleagues describe how to calculate the sample size required for external validation studies, and propose to avoid rules of thumb by tailoring calculations to the model and setting at hand. External validation studies evaluate the performance of one or more prediction models (eg, developed previously using statistical, machine learning, or artificial intelligence approa...
External validation studies are an important but often neglected part of prediction model research. In this article, the second in a series on model evaluation, Riley and colleagues explain what an external validation study entails and describe the key steps involved, from establishing a high quality dataset to evaluating a model’s predictive performance and clinical usefulness. A clinical prediction model is used to calculate predictions for an individual conditional on their characteristics. Such predictions might be of a continuous value (eg, blood pressure, fat mass) or the probability o...
Evaluating the performance of a clinical prediction model is crucial to establish its predictive accuracy in the populations and settings intended for use. In this article, the first in a three part series, Collins and colleagues describe the importance of a meaningful evaluation using internal, internal-external, and external validation, as well as exploring heterogeneity, fairness, and generalisability in model performance. Healthcare decisions for individuals are routinely made on the basis of risk or probability.1 Whether this probability is that a specific outcome or disease is present (d...