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皮肤病学中的人工智能:肤色皮肤的进步和挑战
Rebecca Fliorent1, Brian Fardman1, Alicia Podwojniak1
1Rowan-Virtua School of Osteopathic Medicine, Stratford, NJ, USA.
International journal of dermatology
|March 6, 2024
概括
人工智能 (AI) 工具在皮肤病学方面表现有前途,但由于代表性不足的数据,在诊断肤色 (SOC) 上扎. 需要进一步的研究来提高所有肤色的AI准确性.
科学领域:
- 皮肤病学 皮肤病学
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 在皮肤病学中越来越多地用于评估,诊断和治疗皮肤疾病.
- 人工智能工具为改善皮肤病护理提供了潜力,但它们在不同人群中的有效性令人担忧.
研究的目的:
- 审查当前在皮肤病学中的AI应用.
- 确定AI在诊断肤色 (SOC) 的挑战.
- 提出人工智能在皮肤病学实践中的未来方向.
主要方法:
- 使用PubMed和谷歌学者进行了一项文献审查.
- 搜索了近期 (10年至2023年10月) 关于皮肤病学AI的文献.
- 专注于人工智能在肤色的应用和挑战.
主要成果:
- 目前的AI程序在识别SOC上的病变时的准确性较低.
- SOC在数据集中的代表性不足以及图像质量/标准化问题是关键的挑战.
- 只有30%的AI程序报告了在SOC中的使用数据.
结论:
- 人工智能数据集的显著改进是必要的,以准确地表示更深色肤色.
- 进一步的研究对于验证AI在诊断和治疗SOC患者的有效性至关重要.
- 增强人工智能算法和数据集对于公平的皮肤病护理至关重要.
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