Artificial Intelligence and Chest Imaging. Will Deep Learning Make Us Smarter?
作者信息
Labaki Wassim W, Han MeiLan K
机构信息
1 Division of Pulmonary and Critical Care Medicine University of Michigan Ann Arbor, Michigan.
出版信息
Am J Respir Crit Care Med. 2018 Jan 15;197(2):148-150. doi: 10.1164/rccm.201709-1879ED.
Abstract
摘要
相似文献
1
Artificial Intelligence and Chest Imaging. Will Deep Learning Make Us Smarter?人工智能与胸部成像。深度学习会让我们更聪明吗？
Am J Respir Crit Care Med. 2018 Jan 15;197(2):148-150. doi: 10.1164/rccm.201709-1879ED.
2
Recent advances in artificial intelligence for cardiac CT: Enhancing diagnosis and prognosis prediction.人工智能在心脏 CT 中的最新进展：提高诊断和预后预测能力。
Diagn Interv Imaging. 2023 Nov;104(11):521-528. doi: 10.1016/j.diii.2023.06.011. Epub 2023 Jul 4.
3
Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography.利用胸部计算机断层扫描中的深度学习对吸烟者进行疾病分期和预后评估。
Am J Respir Crit Care Med. 2018 Jan 15;197(2):193-203. doi: 10.1164/rccm.201705-0860OC.
4
Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.利用深度学习技术从急诊初始胸部 X 光片中自动诊断和预测 COVID-19 肺炎。
BMC Infect Dis. 2022 Jul 21;22(1):637. doi: 10.1186/s12879-022-07617-7.
5
Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.人工智能深度学习重建算法对 CT 图像质量和潜在剂量降低的影响：一项体模研究。
Med Phys. 2022 Aug;49(8):5052-5063. doi: 10.1002/mp.15807. Epub 2022 Jun 24.
6
Artificial Intelligence With Deep Learning Enables Assessment of Aortic Aneurysm Diameter and Volume Through Different Computed Tomography Phases.基于深度学习的人工智能可通过不同的计算机断层扫描阶段评估主动脉瘤的直径和体积。
Eur J Vasc Endovasc Surg. 2024 Sep;68(3):408-409. doi: 10.1016/j.ejvs.2024.04.004. Epub 2024 Apr 16.
7
Evaluation of the Effectiveness of Artificial Intelligence Chest CT Lung Nodule Detection Based on Deep Learning.基于深度学习的人工智能胸部 CT 肺结节检测效果评估。
J Healthc Eng. 2021 Aug 17;2021:9971325. doi: 10.1155/2021/9971325. eCollection 2021.
8
Artificial intelligence in lung cancer: current applications and perspectives.人工智能在肺癌中的应用：现状与展望。
Jpn J Radiol. 2023 Mar;41(3):235-244. doi: 10.1007/s11604-022-01359-x. Epub 2022 Nov 9.
9
The promise of artificial intelligence and deep learning in PET and SPECT imaging.人工智能和深度学习在 PET 和 SPECT 成像中的应用前景。
Phys Med. 2021 Mar;83:122-137. doi: 10.1016/j.ejmp.2021.03.008. Epub 2021 Mar 22.
10
Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.基于胸部 X 光片和临床数据的人工智能预测 COVID-19 患者的预后：一项回顾性研究。
Lancet Digit Health. 2021 May;3(5):e286-e294. doi: 10.1016/S2589-7500(21)00039-X. Epub 2021 Mar 24.
引用本文的文献
1
A 3D-CNN model with CT-based parametric response mapping for classifying COPD subjects.基于 CT 的参数响应映射的 3D-CNN 模型用于分类 COPD 患者。
Sci Rep. 2021 Jan 8;11(1):34. doi: 10.1038/s41598-020-79336-5.
2
Quantitative Emphysema on Low-Dose CT Imaging of the Chest and Risk of Lung Cancer and Airflow Obstruction: An Analysis of the National Lung Screening Trial.胸部低剂量 CT 成像定量肺气肿与肺癌及气流阻塞风险：国家肺癌筛查试验分析。
Chest. 2021 May;159(5):1812-1820. doi: 10.1016/j.chest.2020.12.004. Epub 2020 Dec 14.
3
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19.深度学习在肺部医学成像中的应用：关于COVID-19的最新进展与见解
Mach Vis Appl. 2020;31(6):53. doi: 10.1007/s00138-020-01101-5. Epub 2020 Jul 28.
4
Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study.深度学习（三维卷积神经网络）在预测肺腺癌病理侵袭性中的应用：一项初步研究。
Medicine (Baltimore). 2019 Jun;98(25):e16119. doi: 10.1097/MD.0000000000016119.
5
Update in Chronic Obstructive Pulmonary Disease 2018.2018年慢性阻塞性肺疾病的最新进展
Am J Respir Crit Care Med. 2019 Jun 15;199(12):1462-1470. doi: 10.1164/rccm.201902-0374UP.
本文引用的文献
1
Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography.利用胸部计算机断层扫描中的深度学习对吸烟者进行疾病分期和预后评估。
Am J Respir Crit Care Med. 2018 Jan 15;197(2):193-203. doi: 10.1164/rccm.201705-0860OC.
2
The Role of Chest Computed Tomography in the Evaluation and Management of the Patient with Chronic Obstructive Pulmonary Disease.胸部计算机断层扫描在慢性阻塞性肺疾病患者评估与管理中的作用
Am J Respir Crit Care Med. 2017 Dec 1;196(11):1372-1379. doi: 10.1164/rccm.201703-0451PP.
3
Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.胸部放射摄影中的深度学习：使用卷积神经网络自动分类肺结核。
Radiology. 2017 Aug;284(2):574-582. doi: 10.1148/radiol.2017162326. Epub 2017 Apr 24.
4
Dermatologist-level classification of skin cancer with deep neural networks.基于深度神经网络的皮肤癌皮肤科医生级分类。
Nature. 2017 Feb 2;542(7639):115-118. doi: 10.1038/nature21056. Epub 2017 Jan 25.
5
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.深度学习算法在视网膜眼底照片糖尿病视网膜病变检测中的开发与验证。
JAMA. 2016 Dec 13;316(22):2402-2410. doi: 10.1001/jama.2016.17216.
6
Association between Functional Small Airway Disease and FEV1 Decline in Chronic Obstructive Pulmonary Disease.慢性阻塞性肺疾病中功能性小气道疾病与第一秒用力呼气容积下降之间的关联
Am J Respir Crit Care Med. 2016 Jul 15;194(2):178-84. doi: 10.1164/rccm.201511-2219OC.
7
Deep learning.深度学习。
Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539.
8
Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression.基于计算机断层扫描的生物标志物为 COPD 表型和疾病进展的诊断提供了独特的特征。
Nat Med. 2012 Nov;18(11):1711-5. doi: 10.1038/nm.2971. Epub 2012 Oct 7.
9
Heterogeneity of pulmonary perfusion as a mechanistic image-based phenotype in emphysema susceptible smokers.肺气肿易感性吸烟者肺部灌注异质性的基于影像学的机制表型。
Proc Natl Acad Sci U S A. 2010 Apr 20;107(16):7485-90. doi: 10.1073/pnas.0913880107. Epub 2010 Apr 5.
10
Genetic epidemiology of COPD (COPDGene) study design.COPD（COPDGene）遗传流行病学研究设计。
COPD. 2010 Feb;7(1):32-43. doi: 10.3109/15412550903499522.
Zotero 插件