COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning.

Mahyar Salek¹, Nianzhen Li², Hou-Pu Chou², Kiran Saini², Andreja Jovic², Kevin B Jacobs², Chassidy Johnson², Vivian Lu², Esther J Lee², Christina Chang², Phuc Nguyen², Jeanette Mei², Krishna P Pant², Amy Y Wong-Thai², Quillan F Smith², Stephanie Huang², Ryan Chow², Janifer Cruz², Jeff Walker², Bryan Chan², Thomas J Musci², Euan A Ashley^2,3, Maddison Mahdokht Masaeli²

¹Deepcell Inc; 4025 Bohannon Dr., Menlo Park, CA, 94025, USA. yar@deepcellbio.com.

²Deepcell Inc; 4025 Bohannon Dr., Menlo Park, CA, 94025, USA.

³Department of Medicine, Genetics, & Biomedical Data Science, Stanford University, Stanford, CA, USA.

PubMed PMC DOI PDF

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 interpreta…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.