TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods bmj.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from bmj.com Daily Mail and Mail on Sunday newspapers.
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 of a particular event occurring (eg, disease recurrence), and are often in the context of a particular time point (eg, probability of disease recurrence within the next 12 months). Clinical prediction models are traditionally based on a regression equation but are increasingly derived using artificial intelligence or machine learning methods (eg, random forests, neural networks). Regardless of the