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Use of artificial intelligence in emergency radiology: An overview of current applications, challenges, and opportunities.
Al-Dasuqi, Khalid; Johnson, Michele H; Cavallo, Joseph J.
Affiliation
  • Al-Dasuqi K; Department of Radiology and Biomedical Imaging, Yale School of Medicine, Box 208042, Tompkins East 2, 333 Cedar St, New Haven, CT 06520-8042, United States of America. Electronic address: khalid.aldasuqi@yale.edu.
  • Johnson MH; Department of Radiology and Biomedical Imaging, Yale School of Medicine, Box 208042, Tompkins East 2, 333 Cedar St, New Haven, CT 06520-8042, United States of America. Electronic address: michele.h.johnson@yale.edu.
  • Cavallo JJ; Department of Radiology and Biomedical Imaging, Yale School of Medicine, Box 208042, Tompkins East 2, 333 Cedar St, New Haven, CT 06520-8042, United States of America. Electronic address: joseph.cavallo@yale.edu.
Clin Imaging ; 89: 61-67, 2022 Sep.
Article in En | MEDLINE | ID: mdl-35716432
ABSTRACT
The value of artificial intelligence (AI) in healthcare has become evident, especially in the field of medical imaging. The accelerated pace and acuity of care in the Emergency Department (ED) has made it a popular target for artificial intelligence-driven solutions. Software that helps better detect, report, and appropriately guide management can ensure high quality patient care while enabling emergency radiologists to better meet the demands of quick turnaround times. Beyond diagnostic applications, AI-based algorithms also have the potential to optimize other important steps within the ED imaging workflow. This review will highlight the different types of AI-based applications currently available for use in the ED, as well as the challenges and opportunities associated with their implementation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Artificial Intelligence Limits: Humans Language: En Journal: Clin Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2022 Document type: Article Country of publication: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Artificial Intelligence Limits: Humans Language: En Journal: Clin Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2022 Document type: Article Country of publication: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA