The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not. Listen to the audio abstract of this contribution. Artificial intelligence (AI) and its subdiscipline machine learning are receiving increasing attention throughout medicine, including cardiovascular medicine.1,2 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.

Combining self-reported symptoms with Artificial Intelligence can predict the early symptoms of Covid-19, according to research led by scientists at Kings College London. Previous studies have predicted whether people will develop Covid using symptoms from the peak of viral infection, which can be less relevant over time -- fever is common during later phases, for instance. The new study reveals which symptoms of infection can be used for early detection of the disease. Published in the journal The Lancet Digital Health, the research used data collected via the ZOE COVID Symptom Study smartphone app. Each app user logged any symptoms that they experienced over the first 3 days, plus the result of a subsequent PCR test for Coronavirus and personal information like age and sex.