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在皮肤癌查和诊断中整合人工智能:有效性,挑战和未来方向

Vivian Utti^1,2, Vasiliki Bikia^1,3, Ank A Agarwal⁴

¹1Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California, USA;

Annual review of biomedical data science

|May 1, 2025

概括

人工智能 (AI) 可以改善皮肤癌查和诊断,但诸如偏见和验证等挑战阻碍了其使用. 未来的人工智能开发应该专注于可靠性和整合临床背景,以便更好地诊断.

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:

全球皮肤癌的发病率正在上升,造成严重的健康和经济负担.
皮肤病护理的短缺和保险获取障碍限制了患者的治疗.
人工智能 (AI) 为提高皮肤癌查和诊断提供了潜在的解决方案.

研究的目的:

审查在皮肤病学中部署人工智能的挑战和局限性.
探索人工智能在皮肤癌诊断中的未来方向,包括远程皮肤学和视觉语言模型 (VLMs).

主要方法:

对皮肤病学中人工智能应用的文献评论.
分析临床验证,算法偏见,监管监督和患者接受方面的挑战.
探索新兴技术,如远程皮肤学和VLMs.

主要成果:

人工智能有望提高诊断准确度,并扩大皮肤病治疗的机会.
显著的挑战阻碍了人工智能的广泛采用,包括临床验证,偏见和监管障碍.
关于访问差异和算法公平性的伦理问题需要仔细考虑.

结论:

远程皮肤病学和VLM的进步为皮肤病学中的AI提供了未来的潜力.
未来的研究必须优先考虑VLM可靠性,可解释性和与临床背景的整合.
人工智能系统应该协助,而不是取代临床医生,以确保准确和及时的皮肤癌诊断.

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