AI Medical Compendium Journal:
Lab on a chip

Showing 11 to 20 of 69 articles

Is AI essential? Examining the need for deep learning in image-activated sorting of .

Lab on a chip
Artificial intelligence (AI) has become a focal point across a multitude of societal sectors, with science not being an exception. Particularly in the life sciences, imaging flow cytometry has increasingly integrated AI for automated management and c...

Artificial intelligence-accelerated high-throughput screening of antibiotic combinations on a microfluidic combinatorial droplet system.

Lab on a chip
Microfluidic platforms have been employed as an effective tool for drug screening and exhibit the advantages of lower reagent consumption, higher throughput and a higher degree of automation. Despite the great advancement, it remains challenging to s...

Programmable magnetic robot (ProMagBot) for automated nucleic acid extraction at the point of need.

Lab on a chip
Upstream sample preparation remains the bottleneck for point-of-need nucleic acid testing due to its complexity and time-consuming nature. Sample preparation involves extracting, purifying, and concentrating nucleic acids from various matrices. These...

Micro-/nanoscale robotics for chemical and biological sensing.

Lab on a chip
The field of micro-/nanorobotics has attracted extensive interest from a variety of research communities and witnessed enormous progress in a broad array of applications ranging from basic research to global healthcare and to environmental remediatio...

Real-time fluorescence imaging flow cytometry enabled by motion deblurring and deep learning algorithms.

Lab on a chip
Fluorescence imaging flow cytometry (IFC) has been demonstrated as a crucial biomedical technique for analyzing specific cell subpopulations from heterogeneous cellular populations. However, the high-speed flow of fluorescent cells leads to motion bl...

Blood quality evaluation on-chip classification of cell morphology using a deep learning algorithm.

Lab on a chip
The quality of red blood cells (RBCs) in stored blood has a direct impact on the recovery of patients treated by blood transfusion, which directly reflects the quality of blood. The traditional means for blood quality evaluation involve the use of re...

Moving perfusion culture and live-cell imaging from lab to disc: proof of concept toxicity assay with AI-based image analysis.

Lab on a chip
, cell-based assays are essential in diagnostics and drug development. There are ongoing efforts to establish new technologies that enable real-time detection of cell-drug interaction during culture under flow conditions. Our compact (10 × 10 × 8.5 c...

Optofluidic imaging meets deep learning: from merging to emerging.

Lab on a chip
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microsco...

Analyzing angiogenesis on a chip using deep learning-based image processing.

Lab on a chip
Angiogenesis, the formation of new blood vessels from existing vessels, has been associated with more than 70 diseases. Although numerous studies have established angiogenesis models, only a few indicators can be used to analyze angiogenic structures...

Cell deformability heterogeneity recognition by unsupervised machine learning from in-flow motion parameters.

Lab on a chip
Cell deformability is a well-established marker of cell states for diagnostic purposes. However, the measurement of a wide range of different deformability levels is still challenging, especially in cancer, where a large heterogeneity of rheological/...