Detection of Human Bladder Epithelial Cancerous Cells with Atomic Force Microscopy and Machine Learning
The development of noninvasive methods for bladder cancer identification remains a critical clinical need. Recent studies have shown that atomic force microscopy (AFM), combined with pattern recognition machine learning, can detect bladder cancer by analyzing cells extracted from urine. However, the...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
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Series: | Cells |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4409/14/1/14 |
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