Combining MALDI-MS with machine learning for metabolomic characterization of lung cancer patient sera

An increasing amount of evidence has proven that serum metabolites can instantly reflect disease states. Therefore, sensitive and reproducible detection of serum metabolites in a high-throughput manner is urgently needed for clinical diagnosis. Matrix-assisted laser desorption/ionization mass spectr...

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Veröffentlicht in:	Analytical methods 2022-02, Vol.14 (5), p.499-57
Hauptverfasser:	Lai, Xiaopin, Guo, Kunbin, Huang, Wei, Su, Yang, Chen, Siyu, Li, Qiongdan, Liang, Kaiqing, Gao, Wenhua, Wang, Xin, Chen, Yuping, Wang, Hongbiao, Lin, Wen, Wei, Xiaolong, Ni, Wenxiu, Lin, Yan, Jiang, Dazhi, Cheng, Yu-Hong, Che, Chi-Ming, Ng, Kwan-Ming
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomarkers Data processing Fluctuations Humans Ionization Ions Learning algorithms Lung cancer Lung Neoplasms - diagnosis Machine Learning Mass spectrometry Mass spectroscopy Metabolites Metabolomics Metabolomics - methods Patients Signal processing Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization - methods Statistical analysis
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