Several algorithms are commonly used in predictive models for histology, including:
1. Convolutional Neural Networks (CNNs): Highly effective for image analysis tasks due to their ability to capture spatial hierarchies in images. 2. Support Vector Machines (SVMs): Useful for classification tasks in histology. 3. Random Forests: Provide robust predictions by combining the outputs of multiple decision trees. 4. K-Nearest Neighbors (KNN): Simple yet effective for certain types of histological data.
