A review on recent advances of AI-integrated microfluidics for analytical and bioanalytical applications

Document Type

Article

Publication Date

12-1-2024

Abstract

In today's biomedical research, the pursuit of diagnostic tools boasting maximum precision and accuracy while minimizing sample volume and pre-treatment requirements, has intensified. In this regard, microfluidic devices offer promising solutions by reducing sample size and overall research costs. However, the intricate and time-consuming nature of the data obtained from such devices poses significant challenges. To overcome these difficulties, researchers have increasingly turned to the integration of artificial intelligence (AI) with microfluidic platforms, resulting in the emergence of “AI-integrated microfluidics”. Recent advances in computer-related fields can transform AI from a theoretical science to a useful tool for various studies which is anticipated to become an integral part of human life. This review provides a comprehensive overview of various approaches for combining AI algorithms with microfluidic platforms for analytical and bioanalytical assessments. Highlighting applications ranging from cell classification and disease detection to point-of-care diagnostics, the paper underscores the transformative potential of AI-integrated microfluidics in advancing biomedical research and clinical diagnostics.

Identifier

85205700529 (Scopus)

Publication Title

TrAC - Trends in Analytical Chemistry

External Full Text Location

https://doi.org/10.1016/j.trac.2024.118004

e-ISSN

18793142

ISSN

01659936

Volume

181

Grant

43003221

Fund Ref

Shahid Beheshti University of Medical Sciences

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