Establishment and validation of an AI-aid method in the diagnosis of myocardial perfusion imaging.

ABSTRACT:

Background

This study aimed to develop and validate an AI (artificial intelligence)-aid method in myocardial perfusion imaging (MPI) to differentiate ischemia in coronary artery disease.

Methods

We retrospectively selected 599 patients who had received gated-MPI protocol. Images were acquired using hybrid SPECT-CT systems. A training set was used to train and develop the neural network and a validation set was used to test the predictive ability of the neural network. We used a learning technique named "YOLO" to carry out the training process. We compared the predictive accuracy of AI with that of physician interpreters (beginner, inexperienced, and experienced interpreters).

Results

Training performance showed that the accuracy ranged from 66.20% to 94.64%, the recal

SUBMITTER: Zhang R 

PROVIDER: S-EPMC10273563 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature