Quantitative proteomics reveals pregnancy prognosis signature of polycystic ovary syndrome women based on machine learning
AbstractObjective We aimed to screen and construct a predictive model for pregnancy loss in polycystic ovary syndrome (PCOS) patients through machine learning methods.Methods We obtained the endometrial samples from 33 PCOS patients and 7 healthy controls at the Reproductive Center of the Second Hos...
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| Main Authors: | , , , |
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| Format: | Book |
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Taylor & Francis Group,
2024-03-01T00:00:00Z.
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Internet
Connect to this object online.3rd Floor Main Library
| Call Number: |
A1234.567 |
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| Copy 1 | Available |