The benefits of artificial intelligence (AI) human partnerships-evaluating how AI agents enhance expert human performance-are increasingly studied. Though rarely evaluated in healthcare, an inverse approach is possible: AI benefiting from the support of an expert human agent. Here, we investigate both human-AI clinical partnership paradigms in the magnetic resonance imaging-guided characterisation of patients with brain tumours. We reveal that human-AI partnerships improve accuracy and metacognitive ability not only for radiologists supported by AI, but also for AI agents supported by radiologists. Moreover, the greatest patient benefit was evident with an AI agent supported by a human one. Synergistic improvements in agent accuracy, metacognitive performance, and inter-rater agreement suggest that AI can create more capable, confident, and consistent clinical agents, whether human or model-based. Our work suggests that the maximal value of AI in healthcare could emerge not from replacing human intelligence, but from AI agents that routinely leverage and amplify it.


翻译:人工智能(AI)与人类协作的益处——即评估AI智能体如何提升专家人类表现——正日益受到研究关注。尽管在医疗健康领域鲜有评估,但反向研究路径是可行的:AI可从专家人类智能体的支持中获益。本研究在脑肿瘤患者的磁共振成像引导表征任务中,同时探究了两种人机临床协作范式。我们发现,人机协作不仅提升了受AI支持的放射科医生的准确性与元认知能力,也提升了受放射科医生支持的AI智能体的性能。此外,当AI智能体获得人类支持时,患者获益最为显著。智能体准确性、元认知表现及评估者间一致性的协同改善表明,AI能够创造出更具能力、更自信且更一致的临床智能体——无论其是人类还是基于模型的智能体。我们的工作表明,AI在医疗健康领域的最大价值可能并非源于取代人类智能,而是来自那些能够常规化利用并增强人类智能的AI智能体。

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人工智能杂志AI(Artificial Intelligence)是目前公认的发表该领域最新研究成果的主要国际论坛。该期刊欢迎有关AI广泛方面的论文,这些论文构成了整个领域的进步,也欢迎介绍人工智能应用的论文,但重点应该放在新的和新颖的人工智能方法如何提高应用领域的性能,而不是介绍传统人工智能方法的另一个应用。关于应用的论文应该描述一个原则性的解决方案,强调其新颖性,并对正在开发的人工智能技术进行深入的评估。 官网地址:http://dblp.uni-trier.de/db/journals/ai/
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