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Microfluidic Analytical Techniques

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Deep learning-assisted ultra-accurate smartphone testing of paper-based colorimetric ELISA assays.

Analytica chimica acta
Smartphone has long been considered as one excellent platform for disease screening and diagnosis, especially when combined with microfluidic paper-based analytical devices (μPADs) that feature low cost, ease of use, and pump-free operations. In this...

Multicolor-Assay-on-a-Chip Processed by Robotic Operation (MACpro) with Improved Diagnostic Accuracy for Field-Deployable Detection.

Analytical chemistry
The ability to deploy decentralized laboratories with autonomous and reliable disease diagnosis holds the potential to deliver accessible healthcare services for public safety. While microfluidic technologies provide precise manipulation of small flu...

Deep learning-enabled detection of rare circulating tumor cell clusters in whole blood using label-free, flow cytometry.

Lab on a chip
Metastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs r...

GNN-Based Concentration Prediction With Variable Input Flow Rates for Microfluidic Mixers.

IEEE transactions on biomedical circuits and systems
Recent years have witnessed significant advances brought by microfluidic biochips in automating biochemical protocols. Accurate preparation of fluid samples is an essential component of these protocols, where concentration prediction and generation a...

Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.

Lab on a chip
Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic plat...

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

ACS nano
CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput,...

Integrating machine learning and biosensors in microfluidic devices: A review.

Biosensors & bioelectronics
Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research to Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvir...

A Single-Cell Interrogation System from Scratch: Microfluidics and Deep Learning.

The journal of physical chemistry. B
Live-cell imaging using fluorescence microscopy enables researchers to study cellular processes in unprecedented detail. These techniques are becoming increasingly popular among microbiologists. The emergence of microfluidics and deep learning has si...

Microfluidic Optical Aptasensor for Small Molecules Based on Analyte-Tuned Growth of Gold Nanoseeds and Machine Learning-Enhanced Spectrum Analysis: Rapid Detection of Mycotoxins.

ACS sensors
Natural toxins, mainly small molecules, are a category of chemical hazards in agri-food systems that pose threats to both public health and food security. Current standard methods for monitoring these toxins, predominantly based on liquid chromatogra...

Machine Learning-Enhanced Predictive Modeling for Arbitrary Deterministic Lateral Displacement Design and Test.

IEEE transactions on nanobioscience
The separation of biological particles like cells and macromolecules from liquid samples is vital in clinical medicine, supporting liquid biopsies and diagnostics. Deterministic Lateral Displacement (DLD) is prominent for sorting particles in microfl...