Cardiac Rhythm Device Identification Using Neural Networks.

ABSTRACT:

Objectives

This paper reports the development, validation, and public availability of a new neural network-based system which attempts to identify the manufacturer and even the model group of a pacemaker or defibrillator from a chest radiograph.

Background

Medical staff often need to determine the model of a pacemaker or defibrillator (cardiac rhythm device) quickly and accurately. Current approaches involve comparing a device's radiographic appearance with a manual flow chart.

Methods

In this study, radiographic images of 1,676 devices, comprising 45 models from 5 manufacturers were extracted. A convolutional neural network was developed to classify the images, using a training set of 1,451 images. The testing set contained an additional 225 images consisting of 5 ex

SUBMITTER: Howard JP 

PROVIDER: S-EPMC6537849 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature