Machine-learning screening of luminogens with aggregation-induced emission characteristics for fluorescence imaging.

ABSTRACT: Due to the excellent biocompatible physicochemical performance, luminogens with aggregation-induced emission (AIEgens) characteristics have played a significant role in biomedical fluorescence imaging recently. However, screening AIEgens for special applications takes a lot of time and efforts by using conventional chemical synthesis route. Fortunately, artificial intelligence techniques that could predict the properties of AIEgen molecules would be helpful and valuable for novel AIEgens design and synthesis. In this work, we applied machine learning (ML) techniques to screen AIEgens with expected excitation and emission wavelength for biomedical deep fluorescence imaging. First, a database of various AIEgens collected from the literature was established. Then, by extracting key features u

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10039567 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature