Enhancing cell characterization with microfluidics and AI: a comprehensive review of mechanical, electrical, and hybrid techniques

Abstract

This paper examines recent advancements in cell characterization using microfluidic devices, emphasizing mechanical, electrical, and hybrid methodologies. These technologies have substantially improved throughput, precision, and the range of cell types they can analyze. Key microfluidic technologies for cell characterization are reviewed, including label-free electrical and mechanical methods designed for high-throughput, real-time analysis. Microfluidic advancements in cell characterization are critically assessed, along with challenges such as operational complexity and the need for more adaptable, user-friendly platforms. The integration of AI and machine learning in microfluidic systems is also discussed, highlighting their crucial role in automating data analysis and enhancing classification accuracy, with implications for personalized medicine and advanced cellular assays.