Automated estimation of cancer cell deformability with machine learning and acoustic trapping
Abstract Cell deformability is a useful feature for diagnosing various diseases (e.g., the invasiveness of cancer cells). Existing methods commonly inflict pressure on cells and observe changes in cell areas, diameters, or thickness according to the degree of pressure. Then, the Young’s moduli (i.e....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-10882-w |