Clinical Implementation of a Combined Artificial Intelligence and Natural Language Processing Quality Assurance Program for Pulmonary Nodule Detection in the Emergency Department Setting-Reference-Cited by-同舟云学术

Clinical Implementation of a Combined Artificial Intelligence and Natural Language Processing Quality Assurance Program for Pulmonary Nodule Detection in the Emergency Department Setting

Published:2023-04 Issue:4 Volume:20 Page:438-445
ISSN:1546-1440
Container-title:Journal of the American College of Radiology
language:en
Short-container-title:Journal of the American College of Radiology

Author:

Cavallo Joseph J.^ORCID,de Oliveira Santo Irene,Mezrich Jonathan L.,Forman Howard P.

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging

Reference17 articles.

1. Prevalence of incidental pulmonary nodules on computed tomography of the thorax in trauma patients;Hammerschlag;Intern Med J,2015

2. Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017;MacMahon;Radiology,2017

3. Artificial intelligence (AI) for lung nodules: from the AJR special series on AI applications;Liu;AJR Am J Roentgenol,2022

4. Use of artificial intelligence in emergency radiology: an overview of current applications, challenges. opportunities;Al-Dasuqi;Clin Imaging,2022

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