Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis

PCA-SVM (principal component analysis-SVM), peak fitting-AUC-SVM (area under the curve) and peak fitting-spectral reconstruction-SVM rendered prediction accuracies of ~52%, ~43%, and 61%, respectively. Peak fitting has the additional benefit of enabling the biological interpretation of Raman scattering peaks by using the area under the curve, although at a loss of general accuracy. The potential of Raman microscopy in biology, in combination with machine learning pipelines, can be applied to a broader field of cell biology, not limited to regulated cell death.