Sezgin Emre
Center for Biobehavioral Health, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.
Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA.
Digit Health. 2023 Jul 2;9:20552076231186520. doi: 10.1177/20552076231186520. eCollection 2023 Jan-Dec.
The utilization of artificial intelligence (AI) in clinical practice has increased and is evidently contributing to improved diagnostic accuracy, optimized treatment planning, and improved patient outcomes. The rapid evolution of AI, especially generative AI and large language models (LLMs), have reignited the discussions about their potential impact on the healthcare industry, particularly regarding the role of healthcare providers. Concerning questions, "can AI replace doctors?" and "will doctors who are using AI replace those who are not using it?" have been echoed. To shed light on this debate, this article focuses on emphasizing the augmentative role of AI in healthcare, underlining that AI is aimed to complement, rather than replace, doctors and healthcare providers. The fundamental solution emerges with the human-AI collaboration, which combines the cognitive strengths of healthcare providers with the analytical capabilities of AI. A human-in-the-loop (HITL) approach ensures that the AI systems are guided, communicated, and supervised by human expertise, thereby maintaining safety and quality in healthcare services. Finally, the adoption can be forged further by the organizational process informed by the HITL approach to improve multidisciplinary teams in the loop. AI can create a paradigm shift in healthcare by complementing and enhancing the skills of healthcare providers, ultimately leading to improved service quality, patient outcomes, and a more efficient healthcare system.
人工智能（AI）在临床实践中的应用有所增加，显然有助于提高诊断准确性、优化治疗方案并改善患者预后。人工智能的快速发展，尤其是生成式人工智能和大语言模型（LLMs），重新引发了关于它们对医疗行业潜在影响的讨论，特别是关于医疗服务提供者的角色。人们反复提及“人工智能能取代医生吗？”以及“使用人工智能的医生会取代不使用它的医生吗？”等相关问题。为了阐明这场辩论，本文着重强调人工智能在医疗保健中的辅助作用，强调人工智能旨在补充而非取代医生和医疗服务提供者。根本的解决方案在于人机协作，即将医疗服务提供者的认知优势与人工智能的分析能力相结合。人在回路（HITL）方法确保人工智能系统由人类专业知识进行指导、沟通和监督，从而维持医疗服务的安全性和质量。最后，通过采用受HITL方法启发的组织流程，可以进一步推动人工智能的应用，以改善回路中的多学科团队。人工智能可以通过补充和提升医疗服务提供者的技能，在医疗保健领域引发范式转变，最终提高服务质量、改善患者预后并打造更高效的医疗系统。
