Levkovich Inbar, Rabin Eyal, Brann Michal, Elyoseph Zohar
The Faculty of Education, Tel Hai College, Upper Galilee, Israel.
Department of Psychology and Education, The Open University of Israel, Ra'anana, Israel.
Digit Health. 2024 Dec 15;10:20552076241294182. doi: 10.1177/20552076241294182. eCollection 2024 Jan-Dec.
Anxiety is prevalent in childhood but often remains undiagnosed due to its physical manifestations and significant comorbidity. Despite the availability of effective treatments, including medication and psychotherapy, research indicates that physicians struggle to identify childhood anxiety, particularly in complex and challenging cases. This study aims to explore the potential effectiveness of artificial intelligence (AI) language models in diagnosing childhood anxiety compared to general practitioners (GPs).
During February 2024, we evaluated the ability of several large language models (LLMs; ChatGPT-3.5 and ChatGPT-4, Claude.AI, Gemini) to identify cases childhood anxiety disorder, compared with reports of GPs.
AI tools exhibited significantly higher rates of identifying anxiety than GPs. Each AI tool accurately identified anxiety in at least one case: Claude.AI and Gemini identified at least four cases, ChatGPT-3 identified three cases, and ChatGPT-4 identified one or two cases. Additionally, 40% of GPs preferred to manage the cases within their practice, often with the help of a practice nurse, whereas AI tools generally recommended referral to specialized mental or somatic health services.
Preliminary findings indicate that LLMs, specifically Claude.AI and Gemini, exhibit notable diagnostic capabilities in identifying child anxiety, demonstrating a comparative advantage over GPs.
焦虑症在儿童中很常见，但由于其身体表现和显著的共病情况，往往仍未得到诊断。尽管有包括药物治疗和心理治疗在内的有效治疗方法，但研究表明，医生在识别儿童焦虑症方面存在困难，尤其是在复杂且具有挑战性的病例中。本研究旨在探讨与全科医生（GP）相比，人工智能（AI）语言模型在诊断儿童焦虑症方面的潜在有效性。
2024年2月期间，我们评估了几个大语言模型（LLM；ChatGPT-3.5、ChatGPT-4、Claude.AI、Gemini）识别儿童焦虑症病例的能力，并与全科医生的报告进行了比较。
人工智能工具识别焦虑症的准确率显著高于全科医生。每个人工智能工具至少在一个病例中准确识别出了焦虑症：Claude.AI和Gemini识别出至少四个病例，ChatGPT-3识别出三个病例，ChatGPT-4识别出一两个病例。此外，40%的全科医生倾向于在其诊所内处理这些病例，通常在实习护士的帮助下进行，而人工智能工具通常建议转诊至专门的精神或躯体健康服务机构。
初步研究结果表明，大语言模型，特别是Claude.AI和Gemini，在识别儿童焦虑症方面具有显著的诊断能力，显示出相对于全科医生的比较优势。
