Implementing AI in clinical practice: Practical insights on integrating AI through digital dashboards and beyond.
作者信息
Baykaner Tina, Noseworthy Peter A, Wan Elaine Y
机构信息
Stanford University, Stanford, California.
Division of Heart Rhythm Services, Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota.
出版信息
Heart Rhythm. 2024 Oct;21(10):e259-e261. doi: 10.1016/j.hrthm.2024.08.003. Epub 2024 Aug 28.
Abstract
摘要
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本文引用的文献
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Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography.机器学习融合框架结合心脏计算机断层扫描预测心房颤动消融结果。
J Cardiovasc Electrophysiol. 2023 May;34(5):1164-1174. doi: 10.1111/jce.15890. Epub 2023 Apr 27.
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Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.机器学习预测心脏再同步治疗反应：改善与现行指南比较。
Circ Arrhythm Electrophysiol. 2019 Jul;12(7):e007316. doi: 10.1161/CIRCEP.119.007316. Epub 2019 Jun 20.
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Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.开发和验证一种基于深度学习的心电图预测高钾血症的模型。
JAMA Cardiol. 2019 May 1;4(5):428-436. doi: 10.1001/jamacardio.2019.0640.
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Publisher Correction: Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.出版商更正：使用深度神经网络对动态心电图进行心脏病专家级心律失常检测与分类
Nat Med. 2019 Mar;25(3):530. doi: 10.1038/s41591-019-0359-9.
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Association of of Atrial Fibrillation Clinical Phenotypes With Treatment Patterns and Outcomes: A Multicenter Registry Study.心房颤动临床表型与治疗模式和结局的相关性：一项多中心注册研究。
JAMA Cardiol. 2018 Jan 1;3(1):54-63. doi: 10.1001/jamacardio.2017.4665.
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