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人工智能和黑色素瘤诊断中的新技术:叙述性审查

Sebastian Górecki¹, Aleksandra Tatka¹, James Brusey²

¹Maria Sklodowska-Curie Medical Academy, Al. Solidarności 12, 03-411 Warszawa, Poland.

|December 30, 2025

概括

人工智能 (AI) 正通过整合先进的成像和临床数据来改变黑色素瘤诊断. 这篇评论强调了人工智能.

科学领域:

皮肤病学和人工智能研究
医学成像和诊断医学成像和诊断
计算病理学计算病理学

背景情况:

黑色素瘤诊断依赖于倾向于变化的传统方法.
早期和准确的诊断对于黑色素瘤患者的生存至关重要.
人工智能 (AI) 和先进的成像提供了新的诊断范式.

研究的目的:

审查基于人工智能的黑色素瘤诊断的关键发展.
检查AI与各种非侵入性成像技术的整合.
讨论AI在皮肤病学中的挑战和监管方面.

主要方法:

在黑色素瘤诊断 (2020-2025) 中人工智能进步的叙述性综述.
分析人工智能模型,包括CNN,视觉转换器和多式联网架构.
检查人工智能与反射共焦显微镜,超声波,OCT和3D摄影的整合.

主要成果:

人工智能模型正在从CNN发展到视觉转换器和多式联络方法.
人工智能正在与各种成像模式集成,以提高黑色素瘤检测.
远程皮肤学和移动应用正在利用人工智能来提高诊断的可访问性.

结论:

人工智能显示出改善黑色素瘤诊断和可访问性的巨大潜力.
仍然存在关于数据偏差,概括性和临床验证的挑战.
可解释的人工智能,联合学习和公平实施是未来的方向.

关键词:

人工智能的人工智能是人工智能.临床验证临床验证皮肤显微镜 (dermoscopy) 是一种可以检查皮肤的方法.可以解释的人工智能AI 联合学习的联合学习.黑色素瘤是一种黑色素瘤.光学连贯性断层扫描技术反射共聚焦显微镜反射共聚焦显微镜远程皮肤学远程皮肤学视觉变压器视觉变压器

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