ReviewMicrosystems & nanoengineering2023
Computer vision meets microfluidics: a label-free method for high-throughput cell analysis.
Review in Microsystems & nanoengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 56 citations in OpenAlex.
- Microfluidic diffusional sizing in bioanalysis and biosensing.Lab on a chip · 2026Review
- Systematic modeling of phenotypic drug response profiles in patient-derived organoids.bioRxiv : the preprint server for biology · 2026Article
- Optimized Hough Circle Transform for Automated Microparticle Counting in Microfluidic Platforms.Micromachines · 2026Article
- Modeling glioblastoma relapse in vitro: a critical journey from 2D models to organ-on-chip alternatives.NPJ precision oncology · 2026Review
- Parameter-Reduced YOLOv8n with GhostConv and C3Ghost for Automated Blood Cell Detection.Bioengineering (Basel, Switzerland) · 2026Article
- AI-integrated microfluidics for drug screening: From single cell to organ-on-a-chip.Acta pharmaceutica Sinica. B · 2026Review
- AI and Microfluidics: Unlocking Cellular Motility for Bioengineering.Bioengineering (Basel, Switzerland) · 2026Review
- Droplet Microfluidics: From Generation to Manipulation.Micromachines · 2025Article
- Label-free phenotypic antimicrobial susceptibility testing on microfluidic platforms: a review of advances and translation.Mikrochimica acta · 2025Review
- A portable device for probiotic counting and viability assessment based on microfluidic chip and image recognition.iMetaOmics · 2025Article
- Monitoring proliferation and material production of Cupriavidus necator H16 using cell count and volume measurement.Scientific reports · 2025Article
- Microfluidic Sensors Integrated with Smartphones for Applications in Forensics, Agriculture, and Environmental Monitoring.Micromachines · 2025Review
- Development of an AI model for DILI-level prediction using liver organoid brightfield images.Communications biology · 2025Article
- Inner Ear Multiple Primary Cell Type Detection System.Scientific data · 2025Article
- The Latest Advances in Microfluidic DLD Cell Sorting Technology: The Optimization of Channel Design.Biosensors · 2025Review
- Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues.Journal of imaging · 2025Review
- Pump-Free Microfluidics for Cell Concentration Analysis on Smartphones in Clinical Settings (SmartFlow): Design, Development, and Evaluation.JMIR biomedical engineering · 2024Article
- Non-invasive measurement of wall shear stress in microfluidic chip for osteoblast cell culture using improved depth estimation of defocus particle tracking method.Biomicrofluidics · 2024Article
- Automated Uniform Spheroid Generation Platform for High Throughput Drug Screening Process.Biosensors · 2024Article
- Vibrational imaging of metabolites for improved microbial cell strains.Journal of biomedical optics · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in the life sciences and biology, particularly in the analysis of cell imaging data. Microfluidic chips enable the generation of large amounts of visual data at the single-cell level, while computer vision techniques can rapidly process and analyze these data to extract valuable information about cellular health and function. One of the key advantages of this integrative approach is that it allows for noninvasive and low-damage cellular characterization, which is important for studying delicate or fragile microbial cells. The use of microfluidic chips provides a highly controlled environment for cell growth and manipulation, minimizes experimental variability and improves the accuracy of data analysis. Computer vision can be used to recognize and analyze target species within heterogeneous microbial populations, which is important for understanding the physiological status of cells in complex biological systems. As hardware and artificial intelligence algorithms continue to improve, computer vision is expected to become an increasingly powerful tool for in situ cell analysis. The use of microelectromechanical devices in combination with microfluidic chips and computer vision could enable the development of label-free, automatic, low-cost, and fast cellular information recognition and the high-throughput analysis of cellular responses to different compounds, for broad applications in fields such as drug discovery, diagnostics, and personalized medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.