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人工智能在肺结节诊治中的应用专家共识(2022年版)

Low-dose computed tomography (CT) for lung cancer screening has been proven to reduce lung cancer deaths in the screening group compared with the control group. The increasing number of pulmonary nodules being detected by CT scans significantly increase the workload of the radiologists for scan inte...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9051301/
https://www.ncbi.nlm.nih.gov/pubmed/35340198
http://dx.doi.org/10.3779/j.issn.1009-3419.2022.102.08
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description Low-dose computed tomography (CT) for lung cancer screening has been proven to reduce lung cancer deaths in the screening group compared with the control group. The increasing number of pulmonary nodules being detected by CT scans significantly increase the workload of the radiologists for scan interpretation. Artificial intelligence (AI) has the potential to increase the efficiency of pulmonary nodule discrimination and has been tested in preliminary studies for nodule management. As more and more artificial AI products are commercialized, the consensus statement has been organized in a collaborative effort by Thoracic Surgery Committee, Department of Simulated Medicine, Wu Jieping Medical Foundation to aid clinicians in the application of AI-assisted management for pulmonary nodules.
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spelling pubmed-90513012022-05-11 人工智能在肺结节诊治中的应用专家共识(2022年版) Zhongguo Fei Ai Za Zhi 专家共识 Low-dose computed tomography (CT) for lung cancer screening has been proven to reduce lung cancer deaths in the screening group compared with the control group. The increasing number of pulmonary nodules being detected by CT scans significantly increase the workload of the radiologists for scan interpretation. Artificial intelligence (AI) has the potential to increase the efficiency of pulmonary nodule discrimination and has been tested in preliminary studies for nodule management. As more and more artificial AI products are commercialized, the consensus statement has been organized in a collaborative effort by Thoracic Surgery Committee, Department of Simulated Medicine, Wu Jieping Medical Foundation to aid clinicians in the application of AI-assisted management for pulmonary nodules. 中国肺癌杂志编辑部 2022-04-20 /pmc/articles/PMC9051301/ /pubmed/35340198 http://dx.doi.org/10.3779/j.issn.1009-3419.2022.102.08 Text en 版权所有©《中国肺癌杂志》编辑部2022 https://creativecommons.org/licenses/by/3.0/This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/.
spellingShingle 专家共识
人工智能在肺结节诊治中的应用专家共识(2022年版)
title 人工智能在肺结节诊治中的应用专家共识(2022年版)
title_full 人工智能在肺结节诊治中的应用专家共识(2022年版)
title_fullStr 人工智能在肺结节诊治中的应用专家共识(2022年版)
title_full_unstemmed 人工智能在肺结节诊治中的应用专家共识(2022年版)
title_short 人工智能在肺结节诊治中的应用专家共识(2022年版)
title_sort 人工智能在肺结节诊治中的应用专家共识(2022年版)
topic 专家共识
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9051301/
https://www.ncbi.nlm.nih.gov/pubmed/35340198
http://dx.doi.org/10.3779/j.issn.1009-3419.2022.102.08
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