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用人工智能指导设计用于生物医学应用的光探针

Pan Tao^1,2, Pengzhan Wang^1,2, Dushuo Feng¹

¹Frontiers Science Center For Transformative Molecules, School of Chemistry and Chemical Engineering, School of Biomedical Engineering, National Center for Translational Medicine, Zhangjiang Institute for Advanced Study, National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, China.

Chemistry (Weinheim an der Bergstrasse, Germany)

|February 20, 2026

概括

人工智能 (AI) 加快了用于生物成像的光探头的设计. 人工智能优化了探测器的性能,并使成像,传感和治疗中的新应用成为可能,克服了传统的局限性.

科学领域:

生物医学工程生物医学工程
化学生物学化学生物学
人工智能的人工智能

背景情况:

光成像 (FLI) 由于其高灵敏度和分辨率,在生物医学研究中至关重要.
光探测器的性能决定了FLI的有效性,但受到实证设计方法的限制.
人工智能 (AI) 为合理的探测器设计和优化提供了一种新的方法.

研究的目的:

为生物成像中的光探针提供人工智能引导的设计策略的全面审查.
阐明用于探测器开发的基于AI的预测框架的工作流程.
讨论人工智能对优化探测器性能及其生物医学应用的影响.

主要方法:

关于在光探测器设计中的人工智能应用的最新文献的审查.
分析AI在预测和优化光物理,准和响应式探测器特征方面的作用.
检查各种生物医学应用中的人工智能引导探头,包括成像,传感和治疗.

主要成果:

人工智能能够快速预测属性,高通量选,以及光探头的反向设计.
人工智能显著提高了光学性能,准特异性和探测器的响应性.
人工智能引导的探测器在先进的生物成像,诊断和治疗干预方面表现有前途.

结论:

人工智能彻底改变了光探测器设计,超越了传统的试错方法.
人工智能有助于为各种生物医学应用开发复杂的探针.
解决人工智能引导探测器设计的当前挑战将加速生物成像的未来进展.

关键词:

人工智能的人工智能是人工智能.生物医学应用程序光探测器的光探测器结构-财产-功能关系.

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