Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs-Reference-Cited by-同舟云学术

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Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs

Published:2024-09-01 Issue:5 Volume:6 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Busch Felix^ORCID,Bressem Keno K.^ORCID,Suwalski Phillip^ORCID,Hoffmann Lena^ORCID,Niehues Stefan M.^ORCID,Poddubnyy Denis^ORCID,Makowski Marcus R.^ORCID,Aerts Hugo J. W. L.^ORCID,Zhukov Andrei^ORCID,Adams Lisa C.^ORCID

Publisher

Radiological Society of North America (RSNA)

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.230502

Reference16 articles.

1. Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach

2. Current and Emerging Indications for Implantable Cardiac Monitors

3. Computer-aided Assessment of Catheters and Tubes on Radiographs: How Good Is Artificial Intelligence for Assessment?

4. Current trends in the use of cardiac implantable electronic devices and interventional electrophysiological procedures in the European Society of Cardiology member countries: 2015 report from the European Heart Rhythm Association

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Smartphone Imaging and AI: A Commentary on Cardiac Device Classification;Radiology: Artificial Intelligence;2024-09-01

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