Published on in Vol 14 (2025)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71726, first published .
Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial

Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial

Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial

Journals

  1. Kagiyama N, Tokodi M, Hathaway Q, Arnaout R, Davies R, Dey D, Duchateau N, Fraser A, Goto S, Jamthikar A, Lam C, Oikonomou E, Ouyang D, Pandey A, Poterucha T, Raisi-Estabragh Z, Strom J, Zhang Q, Yanamala N, Sengupta P. PRIME 2.0: Proposed Requirements for Cardiovascular Imaging-Related Multimodal-AI Evaluation. JACC: Cardiovascular Imaging 2025 View
  2. Soczyńska J, Butyńska K, Dudek M, Gawełczyk W, Woźniak S, Gajewski P. DynamX Bioadaptor as an Emerging and Promising Innovation in Interventional Cardiology. Life 2025;15(10):1549 View