ArticleCommunications biology2023
COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
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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.
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Who cites it
19 citing papers in PubMed.
- Decoding Immune Cell Doublets in Humans: From Artifacts to Insights.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2026Review
- Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy.bioRxiv : the preprint server for biology · 2026Article
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Versatile Image-Assisted Cell Sorting by Selective Trapping with Spatiotemporal Multiparameter Targeting.ACS sensors · 2025Article
- Characterizing Recent PDMS Changes in Electrokinetic-Based Microfluidic Devices' Performance and Manufacturing for Cell Sorting Applications.Electrophoresis · 2025Article
- Clustering cell nuclei on microgrooves for disease diagnosis using deep learning.Scientific reports · 2025Article
- Advances and applications in single-cell and spatial genomics.Science China. Life sciences · 2025Review
- Review
- Optical sorting: past, present and future.Light, science & applications · 2025Review
- Smart CAR-T Nanosymbionts: archetypes and proto-models.Frontiers in immunology · 2025Review
- Cell-mechanical parameter estimation from 1D cell trajectories using simulation-based inference.PloS one · 2025Article
- Review
- Cell sorting based on pulse shapes from angle resolved detection of scattered light.Communications biology · 2024Article
- A graph-learning based model for automatic diagnosis of Sjögren's syndrome on digital pathological images: a multicentre cohort study.Journal of translational medicine · 2024Article
- Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.PLoS computational biology · 2024Article
- Imaging Flow Cytometry and Convolutional Neural Network-Based Classification Enable Discrimination of Hematopoietic and Leukemic Stem Cells in Acute Myeloid Leukemia.International journal of molecular sciences · 2024Article
- Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease.bioRxiv : the preprint server for biology · 2024Article
- Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, CaBiophysical reviews · 2024Review
- Image-Enabled Cell Sorting Using the BD CellView Technology.Methods in molecular biology (Clifton, N.J.) · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cells are the singular building blocks of life, and a comprehensive understanding of morphology, among other properties, is crucial to the assessment of underlying heterogeneity. We developed Computational Sorting and Mapping of Single Cells (COSMOS), a platform based on Artificial Intelligence (AI) and microfluidics to characterize and sort single cells based on real-time deep learning interpretation of high-resolution brightfield images. Supervised deep learning models were applied to characterize and sort cell lines and dissociated primary tissue based on high-dimensional embedding vectors of morphology without the need for biomarker labels and stains/dyes. We demonstrate COSMOS capabilities with multiple human cell lines and tissue samples. These early results suggest that our neural networks embedding space can capture and recapitulate deep visual characteristics and can be used to efficiently purify unlabeled viable cells with desired morphological traits. Our approach resolves a technical gap in the ability to perform real-time deep learning assessment and sorting of cells based on high-resolution brightfield images.
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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 OpenQuestion graph.