Three Reasons Why Artificial Intelligence Might Be the Radiologist’s Best Friend-Reference-Cited by-同舟云学术

Three Reasons Why Artificial Intelligence Might Be the Radiologist’s Best Friend

Published:2020-07 Issue:1 Volume:296 Page:159-160
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

van Rijn Rick R.¹^ORCID,De Luca Alberto¹^ORCID

Affiliation:

1. From the Department of Radiology and Nuclear Medicine, Emma Children’s Hospital-Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands (R.R.v.R.); Department of Neurology, Brain Center Rudolf Magnus, UMC Utrecht, Utrecht, the Netherlands (A.D.L.); and Image Sciences Institute, UMC Utrecht, Utrecht, the Netherlands (A.D.L.).

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2020200855

Reference9 articles.

1. The Coding of Roentgen Images for Computer Analysis as Applied to Lung Cancer

2. Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation

3. Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology

4. Quantification of Thoracic Lymphatic Flow Patterns Using Dynamic Contrast-enhanced MR Lymphangiography

5. Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study

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