Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease
Artificial intelligence (AI) and its subdiscipline machine learning are receiving increasing attention throughout medicine, including cardiovascular medicine.Proponents promise AI will change the way medicine and healthcare is practiced, by making use of technological advancements that allow for collection of increasingly detailed and diverse data and the ever-increasing computational ability to analyse and combine such data. An important part of these promises is the development and implementation of more accurate clinical prediction models (algorithms, tools, or rules, from here onwards simply referred to as prediction models) to improve—or according to some advocates, even revolutionize—screening, diagnosis, and prognostication of diseases. Prediction models usually fall within one of two major categories: diagnostic prediction models that estimate an individual’s probability of a specific health condition being currently present, and prognostic prediction models that estimate the probability of developing a specific health outcome over a specific time period.
