Urinary Proteomic Spectra Analysis Based on Machine Learning for Classification of Kidney Diseases
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ABSTRACT: To extract urinary proteome spectral features based on advanced mass spectrometer and machine learning algorithms, it could get more accurate reporting results for disease classification. We tried to establish a novel diagnosis model of kidney diseases by combining machine learning XGBoost algorithm with complete urinary proteomic information.
INSTRUMENT(S): Orbitrap Fusion Lumos
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Urine
SUBMITTER: Yong Zhang
LAB HEAD: Yong Zhang
PROVIDER: PXD018996 | Pride | 2022-09-13
REPOSITORIES: Pride
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