Adapting ChatGPT for Color Blindness in Medical Education.

IF 3 2区 医学 Q3 ENGINEERING, BIOMEDICAL
Jinge Wang, Thomas C Yu, Michael S Kolodney, Peter L Perrotta, Gangqing Hu
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引用次数: 0

Abstract

Color vision deficiency (CVD) affects a significant portion of the population, yet its impact is often overlooked in medical education, especially in visually demanding specialties like dermatology, pathology, and radiology. In this study, we investigated the potential of ChatGPT to comprehend CVD-simulated images in image-based diagnostic tasks. Notably, the model successfully adapted its diagnostic reasoning to match CVD-modified color perception while preserving high prediction accuracy. These findings highlight the potential of using ChatGPT to foster more inclusive learning environments for individuals with CVD in visually intensive medical specialties.

在医学教育中针对色盲改编 ChatGPT。
色觉缺陷(CVD)影响着相当一部分人,但其影响在医学教育中却常常被忽视,尤其是在皮肤病学、病理学和放射学等对视觉要求较高的专业。在本研究中,我们研究了 ChatGPT 在基于图像的诊断任务中理解 CVD 模拟图像的潜力。值得注意的是,该模型成功地调整了其诊断推理,以匹配 CVD 修改后的颜色感知,同时保持了较高的预测准确性。这些发现凸显了使用 ChatGPT 为视觉密集型医学专业中的心血管疾病患者营造更具包容性的学习环境的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Biomedical Engineering
Annals of Biomedical Engineering 工程技术-工程:生物医学
CiteScore
7.50
自引率
15.80%
发文量
212
审稿时长
3 months
期刊介绍: Annals of Biomedical Engineering is an official journal of the Biomedical Engineering Society, publishing original articles in the major fields of bioengineering and biomedical engineering. The Annals is an interdisciplinary and international journal with the aim to highlight integrated approaches to the solutions of biological and biomedical problems.
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