Artificial intelligence to improve ischemia prediction in Rubidium Positron Emission Tomography-a validation study.

ABSTRACT:

Background

Patients are referred to functional coronary artery disease (CAD) testing based on their pre-test probability (PTP) to search for myocardial ischemia. The recommended prediction tools incorporate three variables (symptoms, age, sex) and are easy to use, but have a limited diagnostic accuracy. Hence, a substantial proportion of non-invasive functional tests reveal no myocardial ischemia, leading to unnecessary radiation exposure and costs. Therefore, preselection of patients before ischemia testing needs to be improved using a more predictive and personalised approach.

Aims

Using multiple variables (symptoms, vitals, ECG, biomarkers), artificial intelligence-based tools can provide a detailed and individualised profile of each patient. This could improve PTP assess

SUBMITTER: Frey SM 

PROVIDER: S-EPMC10713509 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature