Evaluating the Diagnostic Accuracy of ChatGPT-4.0 for Classifying Multimodal Musculoskeletal Masses: A Comparative Study with Human Raters.

IF 1.3 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Wolfram A Bosbach, Luca Schoeni, Claus Beisbart, Jan F Senge, Milena Mitrakovic, Suzanne E Anderson, Ngwe R Achangwa, Eugen Divjak, Gordana Ivanac, Thomas Grieser, Marc-André Weber, Martin H Maurer, Hatice Tuba Sanal, Keivan Daneshvar
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引用次数: 0

Abstract

Novel artificial intelligence tools have the potential to significantly enhance productivity in medicine, while also maintaining or even improving treatment quality. In this study, we aimed to evaluate the current capability of ChatGPT-4.0 to accurately interpret multimodal musculoskeletal tumor cases.We created 25 cases, each containing images from X-ray, computed tomography, magnetic resonance imaging, or scintigraphy. ChatGPT-4.0 was tasked with classifying each case using a six-option, two-choice question, where both a primary and a secondary diagnosis were allowed. For performance evaluation, human raters also assessed the same cases.When only the primary diagnosis was taken into account, the accuracy of human raters was greater than that of ChatGPT-4.0 by a factor of nearly 2 (87% vs. 44%). However, in a setting that also considered secondary diagnoses, the performance gap shrank substantially (accuracy: 94% vs. 71%). Power analysis relying on Cohen's w confirmed the adequacy of the sample set size (n: 25).The tested artificial intelligence tool demonstrated lower performance than human raters. Considering factors such as speed, constant availability, and potential future improvements, it appears plausible that artificial intelligence tools could serve as valuable assistance systems for doctors in future clinical settings. · ChatGPT-4.0 classifies musculoskeletal cases using multimodal imaging inputs.. · Human raters outperform AI in primary diagnosis accuracy by a factor of nearly two.. · Including secondary diagnoses improves AI performance and narrows the gap.. · AI demonstrates potential as an assistive tool in future radiological workflows.. · Power analysis confirms robustness of study findings with the current sample size.. · Bosbach WA, Schoeni L, Beisbart C et al. Evaluating the Diagnostic Accuracy of ChatGPT-4.0 for Classifying Multimodal Musculoskeletal Masses: A Comparative Study with Human Raters. Rofo 2025; DOI 10.1055/a-2594-7085.

评估ChatGPT-4.0对多模态肌肉骨骼肿块分类的诊断准确性:与人类评分者的比较研究。
新型人工智能工具有可能显著提高医学生产力,同时保持甚至提高治疗质量。在本研究中,我们旨在评估ChatGPT-4.0目前准确解释多模态肌肉骨骼肿瘤病例的能力。我们创建了25个病例,每个病例包含来自x射线、计算机断层扫描、磁共振成像或闪烁成像的图像。ChatGPT-4.0的任务是使用六个选项,两个选择的问题对每个病例进行分类,其中允许主要和次要诊断。在绩效评估方面,人类评分员也评估了相同的案例。当只考虑初步诊断时,人类评分者的准确性比ChatGPT-4.0高出近2倍(87%对44%)。然而,在考虑二次诊断的情况下,表现差距大大缩小(准确率:94%对71%)。基于Cohen's w的幂次分析证实了样本集大小的充分性(n: 25)。经过测试的人工智能工具表现出低于人类评分者的表现。考虑到速度、持续可用性和潜在的未来改进等因素,人工智能工具似乎可以在未来的临床环境中作为医生有价值的辅助系统。·ChatGPT-4.0使用多模态成像输入对肌肉骨骼病例进行分类。·人类评分员在初级诊断准确性方面比人工智能高出近两倍。·包括二次诊断提高了AI的性能,缩小了差距。·人工智能显示了在未来放射工作流程中作为辅助工具的潜力。·功率分析证实了当前样本量下研究结果的稳健性。·Bosbach WA, Schoeni L, Beisbart C等。评估ChatGPT-4.0对多模态肌肉骨骼肿块分类的诊断准确性:与人类评分者的比较研究。Rofo 2025;DOI 10.1055 / - 2594 - 7085。
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来源期刊
CiteScore
1.20
自引率
5.60%
发文量
340
期刊介绍: Die RöFo veröffentlicht Originalarbeiten, Übersichtsartikel und Fallberichte aus dem Bereich der Radiologie und den weiteren bildgebenden Verfahren in der Medizin. Es dürfen nur Arbeiten eingereicht werden, die noch nicht veröffentlicht sind und die auch nicht gleichzeitig einer anderen Zeitschrift zur Veröffentlichung angeboten wurden. Alle eingereichten Beiträge unterliegen einer sorgfältigen fachlichen Begutachtung. Gegründet 1896 – nur knapp 1 Jahr nach der Entdeckung der Röntgenstrahlen durch C.W. Röntgen – blickt die RöFo auf über 100 Jahre Erfahrung als wichtigstes Publikationsmedium in der deutschsprachigen Radiologie zurück. Sie ist damit die älteste radiologische Fachzeitschrift und schafft es erfolgreich, lange Kontinuität mit dem Anspruch an wissenschaftliches Publizieren auf internationalem Niveau zu verbinden. Durch ihren zentralen Platz im Verlagsprogramm stellte die RöFo die Basis für das heute umfassende und erfolgreiche Radiologie-Medienangebot im Georg Thieme Verlag. Besonders eng verbunden ist die RöFo mit der Geschichte der Röntgengesellschaften in Deutschland und Österreich. Sie ist offizielles Organ von DRG und ÖRG und die Mitglieder der Fachgesellschaften erhalten die Zeitschrift im Rahmen ihrer Mitgliedschaft. Mit ihrem wissenschaftlichen Kernteil und dem eigenen Mitteilungsteil der Fachgesellschaften bietet die RöFo Monat für Monat ein Forum für den Austausch von Inhalten und Botschaften der radiologischen Community im deutschsprachigen Raum.
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