AIMC Topic: Lab-On-A-Chip Devices

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Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

Lab on a chip Aug 23, 2022
A major challenge in the field of microfluidics is to predict and control drop interactions. This work develops an image-based data-driven model to forecast drop dynamics based on experiments performed on a microfluidics device. Reduced-order modelli...
Deep Learning Microfluidics Lab-On-A-Chip Devices Neural Networks, Computer Algorithms
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Advances in Organ-on-a-Chip Materials and Devices.

ACS applied bio materials Jul 15, 2022
The organ-on-a-chip (OoC) paves a way for biomedical applications ranging from preclinical to clinical translational precision. The current trends in the in vitro modeling is to reduce the complexity of human organ anatomy to the fundamental cellular...
Artificial Intelligence Polymers Lab-On-A-Chip Devices Humans
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Breakthroughs and Applications of Organ-on-a-Chip Technology.

Cells Jun 2, 2022
Organ-on-a-chip (OOAC) is an emerging technology based on microfluid platforms and in vitro cell culture that has a promising future in the healthcare industry. The numerous advantages of OOAC over conventional systems make it highly popular. The chi...
Lab-On-A-Chip Devices Artificial Intelligence Biocompatible Materials Microfluidics Tissue Engineering
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Microfluidic Devices Controlled by Machine Learning with Failure Experiments.

Analytical chemistry Apr 25, 2022
A critical microchannel technique is to isolate specific objects, such as cells, in a biological solution. Generally, this particle sorting is achieved by designing a microfluidic device and tuning its control values; however, unpredictable motions o...
Microfluidic Analytical Techniques Robotics Lab-On-A-Chip Devices Machine Learning
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Microfluidic manipulation by spiral hollow-fibre actuators.

Nature communications Mar 14, 2022
A microfluidic manipulation system that can sense a liquid and control its flow is highly desirable. However, conventional sensors and motors have difficulty fitting the limited space in microfluidic devices; moreover, fast sensing and actuation are ...
Temperature Robotics Microfluidics Lab-On-A-Chip Devices
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Application of NIRs coupled with PLS and ANN modelling to predict average droplet size in oil-in-water emulsions prepared with different microfluidic devices.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 6, 2022
In this study, the potential of microfluidic systems with different microchannel geometries (microchannel with teardrop micromixers and microchannel with swirl micromixers) for the preparation of oil-in-water (O/W) emulsions using two different emuls...
Neural Networks, Computer Water Least-Squares Analysis Emulsions Lab-On-A-Chip Devices
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Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin.

PLoS computational biology Nov 29, 2021
Sickle cell disease, a genetic disorder affecting a sizeable global demographic, manifests in sickle red blood cells (sRBCs) with altered shape and biomechanics. sRBCs show heightened adhesive interactions with inflamed endothelium, triggering painfu...
Erythrocyte Deformability Hemoglobin, Sickle Biophysical Phenomena Lab-On-A-Chip Devices Protein Multimerization Erythrocytes, Abnormal Laminin High-Throughput Screening Assays Image Interpretation, Computer-Assisted Microfluidics Anemia, Sickle Cell Neural Networks, Computer Diagnosis, Computer-Assisted Humans In Vitro Techniques Deep Learning Computational Biology
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Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Scientific reports Jun 30, 2021
Combining microfluidics technology with machine learning represents an innovative approach to conduct massive quantitative cell behavior study and implement smart decision-making systems in support of clinical diagnostics. The spleen plays a key-role...
Erythrocyte Deformability Machine Learning Female Anemia, Hemolytic, Congenital Lab-On-A-Chip Devices Male Image Processing, Computer-Assisted Humans Microfluidic Analytical Techniques Erythrocytes
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Predicting cell behaviour parameters from glioblastoma on a chip images. A deep learning approach.

Computers in biology and medicine Jun 6, 2021
The broad possibilities offered by microfluidic devices in relation to massive data monitoring and acquisition open the door to the use of deep learning technologies in a very promising field: cell culture monitoring. In this work, we develop a metho...
Neural Networks, Computer Brain Neoplasms Humans Glioblastoma Deep Learning Lab-On-A-Chip Devices Image Processing, Computer-Assisted
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Cheetah: A Computational Toolkit for Cybergenetic Control.

ACS synthetic biology Apr 27, 2021
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups ...
Synthetic Biology Computer Systems Lab-On-A-Chip Devices Animals Microscopy Image Processing, Computer-Assisted Software Mouse Embryonic Stem Cells Deep Learning Escherichia coli Reproducibility of Results Mice Data Accuracy Cell Line
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