ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2019
Machine Learning Based Real-Time Image-Guided Cell Sorting and Classification.
Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed, 84 citations in OpenAlex.
- Liquid biopsy: current applications and future directions.Molecular biomedicine · 2026Review
- Intelligent label-free droplet microfluidic sorting system for single-cell encapsulation and morphology-guided screening.Microsystems & nanoengineering · 2026Article
- Revolutionizing Stem Cell Sorting with Machine Learning: A Review of Trends, Tools, and Future Directions.Iranian journal of medical sciences · 2026Review
- Versatile Image-Assisted Cell Sorting by Selective Trapping with Spatiotemporal Multiparameter Targeting.ACS sensors · 2025Article
- Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli.Journal of the Royal Society, Interface · 2025Article
- Optical sorting: past, present and future.Light, science & applications · 2025Review
- Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Review
- Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Imaging Flow Cytometry: Development, Present Applications, and Future Challenges.Methods and protocols · 2024Review
- Article
- Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition.Biomedical microdevices · 2023Article
- Recent advances in droplet sequential monitoring methods for droplet sorting.Biomicrofluidics · 2023Review
- Enhancing single-cell biology through advanced AI-powered microfluidics.Biomicrofluidics · 2023Article
- High-Throughput Single-Cell Analysis of Nanoparticle-Cell Interactions.Trends in analytical chemistry : TRAC · 2023Article
- Machine learning implementation strategy in imaging and impedance flow cytometry.Biomicrofluidics · 2023Review
- Microsystem Advances through Integration with Artificial Intelligence.Micromachines · 2023Review
- Upgraded User-Friendly Image-Activated Microfluidic Cell Sorter Using an Optimized and Fast Deep Learning Algorithm.Micromachines · 2022Article
- A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation.Scientific reports · 2022Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Cell classification based on phenotypical, spatial, and genetic information greatly advances our understanding of the physiology and pathology of biological systems. Technologies derived from next generation sequencing and fluorescent activated cell sorting are cornerstones for cell- and genomic-based assays supporting cell classification and mapping. However, there exists a deficiency in technology space to rapidly isolate cells based on high content image information. Fluorescence-activated cell sorting can only resolve cell-to-cell variation in fluorescence and optical scattering. Utilizing microfluidics, photonics, computation microscopy, real-time image processing and machine learning, we demonstrate an image-guided cell sorting and classification system possessing the high throughput of flow cytometer and high information content of microscopy. We demonstrate the utility of this technology in cell sorting based on (1) nuclear localization of glucocorticoid receptors, (2) particle binding to the cell membrane, and (3) DNA damage induced γ-H2AX foci. © 2019 International Society for Advancement of Cytometry.
Indexed as
Identifiers
What Socratic holds
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.