Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation
Development of an artificial intelligence algorithm for automated detection of cardiovascular intervention-related complications
By Okken A, Wanders R, Klappe A and 6 others.
Abstract
Background
Intervention-related complications negatively affect healthcare quality and costs. Complication registration and reporting play an important role in the improvement of healthcare outcomes but are time-consuming and hampered by under-reporting.
Methods
We developed an artificial intelligence (AI)-aided tool that extracts specific complications, including bleeding, tamponade, CVA and phrenic paralysis, from electronic healthcare records of patients undergoing pulmonary vein isolation (PVI), percutaneous transluminal coronary angioplasty (PTCA) and transcatheter aortic valve implantation (TAVI). Both structured and unstructured data were used, along with additional signals identified through machine learning. The model was optimized to achieve high sensitivity.