Abstract: A method for treatment of a disease by monitoring a progression of the disease includes obtaining image data including a representation of diseased cells of a patient. Based on the type of the disease, one or more features to extract from the image data are determined, the features each representing a physical parameter of at least one of the diseased cells represented in the image data. A feature vector is formed from the extracted features. A machine learning model is selected, and the feature vector is processed using the machine learning model. The machine learning model is trained with labeled image data representing instances of diseased cells having the disease and associating scores representing predicted rates of disease progression with the respective instances of diseased cells having the type of disease. Based on the processing, a score is determined that represents a predicted rate of disease progression indicated by the image data.