2026-10-15T00:38:15Z https://www.scidb.cn/oai

10.57760/sciencedb.msdc.00110 2026-06-16T09:03:52Z

2026-06-16 A High-Quality, Batch-Diverse and Small-SampleBenchmark for Probabilistic-Guided MS Classification doi:10.57760/sciencedb.msdc.00110 en This dataset contains twelve types of raw data acquired by mass spectrometry. After data preprocessing, dimensionality reduction and feature selection, the processed data are obtained. It covers multiple sample types including cells, serum, urine, plasma, gingival crevicular fluid, fecal samples and oil. The dataset has been split into training and test sets with labels assigned, which can be directly used to evaluate the performance of machine learning and deep learning models for classification tasks in artificial intelligence. mass spectrometry; classification; artificial intelligent; deep learning Yinchu Wang Wei Zhang Zilong Liu Lin Guo Xingchuang Xiong PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1021/acs.analchem.5c04933 Science Data Bank