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介入放射学的救星:人工智能对实践的影响。

Interventional Radiology ex-machina: impact of Artificial Intelligence on practice.

机构信息

Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia.

Postgraduation School in Radiodiagnostics, Università Degli Studi di Milano, via Festa del Perdono, 20122, Milan, Italy.

出版信息

Radiol Med. 2021 Jul;126(7):998-1006. doi: 10.1007/s11547-021-01351-x. Epub 2021 Apr 16.


DOI:10.1007/s11547-021-01351-x
PMID:33861421
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8050998/
Abstract

Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic. AI was mainly introduced via artificial neural networks, developed in the early 1950s, and with its evolution into "computational learning models." Machine Learning analyzes and extracts features in larger data after exposure to examples; Deep Learning uses neural networks in order to extract meaningful patterns from imaging data, even deciphering that which would otherwise be beyond human perception. Thus, AI has the potential to revolutionize the healthcare systems and clinical practice of doctors all over the world. This is especially true for radiologists, who are integral to diagnostic medicine, helping to customize treatments and triage resources with maximum effectiveness. Related in spirit to Artificial intelligence are Augmented Reality, mixed reality, or Virtual Reality, which are able to enhance accuracy of minimally invasive treatments in image guided therapies by Interventional Radiologists. The potential applications of AI in IR go beyond computer vision and diagnosis, to include screening and modeling of patient selection, predictive tools for treatment planning and navigation, and training tools. Although no new technology is widely embraced, AI may provide opportunities to enhance radiology service and improve patient care, if studied, validated, and applied appropriately.

摘要

人工智能(AI)是信息学的一个分支,它使用算法来不懈地处理数据,理解其含义并提供所需的结果,不断重新定义其逻辑。AI 主要是通过 20 世纪 50 年代早期开发的人工神经网络引入的,随着其演变为“计算学习模型”。机器学习在暴露于示例后分析和提取更大数据中的特征;深度学习使用神经网络从成像数据中提取有意义的模式,甚至可以破译人类无法感知的模式。因此,人工智能有可能彻底改变全球医疗保健系统和医生的临床实践。对于放射科医生来说尤其如此,他们是诊断医学的重要组成部分,有助于最大限度地提高治疗效果和资源分诊的效率。与人工智能相关的还有增强现实、混合现实或虚拟现实,它们能够通过介入放射科医生提高图像引导治疗中微创手术的准确性。AI 在 IR 中的潜在应用不仅限于计算机视觉和诊断,还包括患者选择的筛选和建模、治疗计划和导航的预测工具以及培训工具。尽管没有一种新技术被广泛接受,但如果经过研究、验证和适当应用,人工智能可能会为放射科服务提供增强机会并改善患者护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/50657f5f7450/11547_2021_1351_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/f4261bd756a7/11547_2021_1351_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/31a7dda80a76/11547_2021_1351_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/e8309269cf2b/11547_2021_1351_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/9a51254536c9/11547_2021_1351_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/50657f5f7450/11547_2021_1351_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/f4261bd756a7/11547_2021_1351_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/31a7dda80a76/11547_2021_1351_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/e8309269cf2b/11547_2021_1351_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/9a51254536c9/11547_2021_1351_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b90/8050998/50657f5f7450/11547_2021_1351_Fig5_HTML.jpg

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Cardiovasc Intervent Radiol. 2019-6-19

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