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人工智能在血管外科中的临床应用

Clinical Applications of Artificial Intelligence in Vascular Surgery.

作者信息

Joh Jin Hyun

机构信息

Department of Surgery, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Korea.

出版信息

Vasc Specialist Int. 2025 Apr 30;41:8. doi: 10.5758/vsi.240120.

DOI:10.5758/vsi.240120
PMID:40302180
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12041748/
Abstract

Artificial intelligence (AI) has been applied in many fields, including science, technology, and medicine. However, vascular surgeons face many obstacles and limitations in using and applying AI because of their limited understanding of computer science, programming languages, and complex AI technologies, such as machine learning, deep learning, and artificial neural networks. This article describes the basic knowledge of AI, applications of AI technologies in vascular surgery, and the use of smart wearable devices. Finally, the challenges and limitations of AI are discussed as essential issues hindering its widespread application in vascular surgery.

摘要

人工智能(AI)已应用于许多领域,包括科学、技术和医学。然而,血管外科医生在使用和应用人工智能时面临许多障碍和限制,因为他们对计算机科学、编程语言以及复杂的人工智能技术(如机器学习、深度学习和人工神经网络)的理解有限。本文介绍了人工智能的基础知识、人工智能技术在血管外科的应用以及智能可穿戴设备的使用。最后,讨论了人工智能的挑战和局限性,这些是阻碍其在血管外科广泛应用的关键问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf8f/12041748/a5d3fbbc9a02/vsi-41-8-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf8f/12041748/545b3e4244f9/vsi-41-8-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf8f/12041748/a5d3fbbc9a02/vsi-41-8-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf8f/12041748/545b3e4244f9/vsi-41-8-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf8f/12041748/a5d3fbbc9a02/vsi-41-8-f2.jpg

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本文引用的文献

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Automating Clinical Trial Matches Via Natural Language Processing of Synthetic Electronic Health Records and Clinical Trial Eligibility Criteria.通过合成电子健康记录和临床试验资格标准的自然语言处理实现临床试验匹配自动化
AMIA Jt Summits Transl Sci Proc. 2024 May 31;2024:125-134. eCollection 2024.
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Addressing 6 challenges in generative AI for digital health: A scoping review.应对数字健康领域生成式人工智能的六大挑战:一项范围综述
PLOS Digit Health. 2024 May 23;3(5):e0000503. doi: 10.1371/journal.pdig.0000503. eCollection 2024 May.
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An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes.
基于人工智能的腹主动脉瘤预后分类器,用于预测患者的预后。
Sci Rep. 2024 Feb 9;14(1):3390. doi: 10.1038/s41598-024-53459-5.
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Artificial Intelligence of Arterial Doppler Waveforms to Predict Major Adverse Outcomes Among Patients Evaluated for Peripheral Artery Disease.利用动脉多普勒波形人工智能预测接受外周动脉疾病评估患者的主要不良结局
J Am Heart Assoc. 2024 Feb 6;13(3):e031880. doi: 10.1161/JAHA.123.031880. Epub 2024 Jan 19.
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Development of an Artificial Intelligence Tool for Intraoperative Guidance During Endovascular Abdominal Aortic Aneurysm Repair.开发一种用于血管内腹主动脉瘤修复术中指导的人工智能工具。
Ann Vasc Surg. 2024 Feb;99:96-104. doi: 10.1016/j.avsg.2023.08.027. Epub 2023 Oct 31.
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Carotid Endarterectomy in the Very Elderly: Short-, Medium-, and Long-Term Outcomes.高龄患者的颈动脉内膜切除术:短期、中期和长期疗效
Vasc Specialist Int. 2023 Sep 25;39:28. doi: 10.5758/vsi.230060.
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Aortic Endograft Infection: Diagnosis and Management.主动脉内移植物感染:诊断与管理
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Artificial intelligence framework to predict wall stress in abdominal aortic aneurysm.预测腹主动脉瘤壁应力的人工智能框架
Appl Eng Sci. 2022 Jun;10. doi: 10.1016/j.apples.2022.100104. Epub 2022 May 2.
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