Group Classification based on Machine Learning Analysis of Mass Spectrometry Data from Sweat

摘要

Machine learning analysis of mass spectrometry spectra from human sweat samples is used to determine characteristics of interest such as age, ethnicity, gender drug use and disease state directly from the m/z data. This avoids the difficult problem of performing a full chemical analysis of human sweat samples to determine the characteristics of interest.