Deterministic Lateral Displacement (DLD) Analysis Tool Utilizing Machine Learning towards High-Throughput Separation.

Deterministic lateral displacement (DLD) is a microfluidic method for the continuous separation of particles based on their size. There is growing interest in using DLD for harvesting circulating tumor cells from blood for further assays due to its low cost and robustness. While DLD is a powerful tool and development of high-throughput DLD separation devices holds great promise in cancer diagnostics and therapeutics, much of the experimental data analysis in DLD research still relies on error-prone and time-consuming manual processes.