The Picasso's skepticism on computer science and the dawn of generative AI: questions after the answers to keep "machines-in-the-loop".

IF 3.7 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING European Radiology Experimental Pub Date : 2024-07-24 DOI:10.1186/s41747-024-00485-7
Filippo Pesapane, Renato Cuocolo, Francesco Sardanelli
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Abstract

Starting from Picasso's quote ("Computers are useless. They can only give you answers"), we discuss the introduction of generative artificial intelligence (AI), including generative adversarial networks (GANs) and transformer-based architectures such as large language models (LLMs) in radiology, where their potential in reporting, image synthesis, and analysis is notable. However, the need for improvements, evaluations, and regulations prior to clinical use is also clear. Integration of LLMs into clinical workflow needs cautiousness, to avoid or at least mitigate risks associated with false diagnostic suggestions. We highlight challenges in synthetic image generation, inherent biases in AI models, and privacy concerns, stressing the importance of diverse training datasets and robust data privacy measures. We examine the regulatory landscape, including the 2023 Executive Order on AI in the United States and the 2024 AI Act in the European Union, which set standards for AI applications in healthcare. This manuscript contributes to the field by emphasizing the necessity of maintaining the human element in medical procedures while leveraging generative AI, advocating for a "machines-in-the-loop" approach.

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毕加索对计算机科学的怀疑论与生成式人工智能的曙光:答案之后的问题,让 "机器在环中"。
从毕加索的名言("计算机是无用的,它们只能给你答案")开始,我们讨论了在放射学中引入生成式人工智能(AI),包括生成式对抗网络(GANs)和基于变换器的架构,如大型语言模型(LLMs),它们在报告、图像合成和分析方面的潜力引人注目。然而,在临床使用之前,显然还需要进行改进、评估和规范。将 LLM 纳入临床工作流程需要谨慎,以避免或至少降低与错误诊断建议相关的风险。我们强调了合成图像生成的挑战、人工智能模型的固有偏差和隐私问题,强调了多样化训练数据集和健全的数据隐私措施的重要性。我们研究了监管情况,包括美国的 2023 年人工智能行政命令和欧盟的 2024 年人工智能法案,这些法案为人工智能在医疗保健领域的应用制定了标准。本手稿强调在利用生成式人工智能的同时,有必要在医疗程序中保留人类元素,倡导 "机器在环 "的方法,从而为该领域做出贡献。
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来源期刊
European Radiology Experimental
European Radiology Experimental Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
6.70
自引率
2.60%
发文量
56
审稿时长
18 weeks
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