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

• Published in: Communications biology Vol. 6; no. 1; p. 971
• Main Authors: Salek, Mahyar, Li, Nianzhen, Chou, Hou-Pu, Saini, Kiran, Jovic, Andreja, Jacobs, Kevin B., Johnson, Chassidy, Lu, Vivian, Lee, Esther J., Chang, Christina, Nguyen, Phuc, Mei, Jeanette, Pant, Krishna P., Wong-Thai, Amy Y., Smith, Quillan F., Huang, Stephanie, Chow, Ryan, Cruz, Janifer, Walker, Jeff, Chan, Bryan, Musci, Thomas J., Ashley, Euan A., Masaeli, Maddison
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group 22.09.2023; Nature Publishing Group UK; Nature Portfolio
• Subjects: Artificial intelligence; Biology; Cell lines; Computer applications; Cytology; Deep learning; Embedding; Mapping; Microfluidics; Morphology; Neural networks

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 Intellig...