Weakly supervised anomaly detection coupled with Fourier transform infrared (FT-IR) spectroscopy for the identification of non-normal tissue

Abstract

A novel weakly supervised anomaly detection machine learning method is used to identify non-normal tissue subgroups, interferents, and other tissue components in IR Micro-spectroscopy liver tissue data when trained on a single control group of data.