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洞察人工智能与我们的智能——肺癌筛查前沿领域

Insights into artificial intelligence and our intelligence-on the frontier of lung cancer screening.

作者信息

Bowers Philippa Jane Temple, Kirk Frazer Michael

机构信息

Cardiothoracic Surgery Department, The Prince Charles Hospital, Chermside, Australia.

School of Medicine and Dentistry, Griffith University, Gold Coast, Australia.

出版信息

J Thorac Dis. 2024 Nov 30;16(11):7905-7909. doi: 10.21037/jtd-24-1077. Epub 2024 Nov 21.

Abstract

This paper explores the potential of artificial intelligence (AI) in lung cancer screening programs, particularly in the interpretation of computed tomography (CT) scans. The authors acknowledge the benefits of AI, including faster and potentially more accurate analysis of scans, but also raise concerns about clinician trust, transparency, and the deskilling of radiologists due to decreased scan exposure. The rise of AI in medicine and the introduction of national lung cancer screening programs are both increasing contemporarily and naturally the overlap and interplay between the two in the future is ensured. The paper highlights the importance of human-AI collaboration, emphasizing the need for interpretable models and ongoing validation through clinical trials. The promising results and problems uncovered the current pilot studies is explored. Building trust with patients and clinicians is also crucial, considering factors like disease risk perception and the human element of patient interaction. The authors conclude that while AI offers significant promise, widespread adoption hinges on addressing ethical considerations and ensuring a balanced, synergistic relationship between AI and medical professionals. This report aims to provide a talking point to inspire conversations around, and prepare clinicians for the rapidly approaching frontier that is AI in healthcare.

摘要

本文探讨了人工智能(AI)在肺癌筛查项目中的潜力,特别是在计算机断层扫描(CT)图像解读方面。作者认可人工智能的优势,包括对扫描图像进行更快且可能更准确的分析,但也对临床医生的信任、透明度以及由于减少扫描图像判读导致放射科医生技能退化表示担忧。医学领域人工智能的兴起与国家肺癌筛查项目的推行同步发展,自然而然地,二者未来的重叠和相互作用也得到了保障。本文强调了人机协作的重要性,着重指出需要可解释的模型,并通过临床试验进行持续验证。文中探讨了当前试点研究中发现的有前景的结果和问题。考虑到疾病风险认知和患者互动中的人文因素等,与患者和临床医生建立信任也至关重要。作者总结称,虽然人工智能前景广阔,但广泛应用取决于解决伦理考量,并确保人工智能与医学专业人员之间建立平衡、协同的关系。本报告旨在提供一个话题切入点,激发相关讨论,并让临床医生为医疗保健领域迅速到来的人工智能前沿做好准备。

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