In histological applications, SVMs take input features extracted from histological stains images, such as color intensities, texture measures, and shape descriptors. These features are fed into the SVM, which then constructs a hyperplane in a high-dimensional feature space to separate different tissue types. For instance, an SVM can be trained to differentiate between benign and malignant cells in cancer histopathology slides.
