Steffen Uhlig

The paper presents a method to detect temporal shifts in MALDI-TOF MS spectral patterns of MRSA/MSSA using CNNs and statistical methods, with GradCam for feature analysis.

This paper evaluates spectral comparison methods for non-targeted analysis, showing neural classification distance outperforms Mahalanobis distance in handling complex spectral data.

This paper develops a mathematical framework and experimental designs for validating binary non-targeted methods to improve their reliability and performance in food fraud detection.

The paper uses AI and non-target mass spectrometry to distinguish wheat and spelt cultivars and validates the method's discriminatory power.