TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

Prediction models are used across different healthcare settings. They are used to estimate an outcome value or risk. Most models estimate the probability of the presence of a particular health condition (diagnostic) or whether a particular outcome will occur in the future (prognostic).1 Their primary use is to support clinical decision making, such as whether to refer patients for further testing, monitor disease deterioration or treatment effects, or initiate treatment or lifestyle changes. Examples of well known prediction models include EuroSCORE II (cardiac surgery),2 the Gail model (breast cancer),3 the Framingham risk score (cardiovascular disease),4 IMPACT (traumatic brain injury),5 and FRAX (osteoporotic and hip fractures).6Prediction models are abundant in the biomedical literature, with thousands of models published annually (and increasing), and have been developed for many outcomes and health conditions.78 At least 731 diagnostic and prognostic prediction model studies on covid-19 were published during the first 12 months of the…
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