Suthar Pokhraj P, Kounsal Avin, Chhetri Lavanya, Saini Divya, Dua Sumeet G
Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, USA.
Department of Clinical Nutrition, Rush University Medical Center, Chicago, USA.
Cureus. 2023 Aug 23;15(8):e43958. doi: 10.7759/cureus.43958. eCollection 2023 Aug.
The advent of artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT 4.0, holds significant potential in healthcare, specifically in radiology. This study examined the accuracy of ChatGPT 4.0 (July 20, 2023, version) in solving diagnostic quizzes from the American Journal of Neuroradiology's (AJNR) "Case of the Month." We evaluated the diagnostic accuracy of ChatGPT 4.0 when provided with a patient's history and imaging findings weekly over four weeks, using 140 cases from the AJNR "Case of the Month" portal (from November 2011 to July 2023). The overall diagnostic accuracy was found to be 57.86% (81 out of 140 cases). The diagnostic performance varied across brain, head and neck, and spine subgroups, with accuracy rates of 54.65%, 67.65%, and 55.0%, respectively. These findings suggest that AI models such as ChatGPT 4.0 could serve as useful adjuncts in radiological diagnostics, thus potentially enhancing patient care and revolutionizing medical education.
人工智能(AI)的出现,尤其是像ChatGPT 4.0这样的大型语言模型(LLM),在医疗保健领域,特别是放射学领域具有巨大潜力。本研究考察了ChatGPT 4.0(2023年7月20日版本)解答美国神经放射学杂志(AJNR)“月度病例”诊断测验的准确性。我们使用来自AJNR“月度病例”门户(2011年11月至2023年7月)的140个病例,在四周内每周向ChatGPT 4.0提供患者病史和影像检查结果,评估其诊断准确性。总体诊断准确率为57.86%(140个病例中的81个)。诊断表现因脑、头颈部和脊柱亚组而异,准确率分别为54.65%、67.65%和55.0%。这些发现表明,像ChatGPT 4.0这样的人工智能模型可以作为放射诊断中的有用辅助工具,从而有可能改善患者护理并彻底改变医学教育。