Image Phenotyping Network (ImPhenet) is a proof-of-concept framework which uses DL to classify the organoids into healthy or DS. The main steps of this software are: AI_ImPhenetModels: Folder with the final trained DL and ML models for day 0 and day 7. Data: Folder with the csv files pointing where the data is stored and some information (label, label encoded, if it has been used for training etc.) FeatureExtraction: Models: NotebooksToRun: Main folder to use. It contains the jupyter notebooks to execute to: 1_ImagePreparation.ipynb: Prepare a new set of images. 2_SubregionSelection.ipynb: Selection of informative subregions. 3_ImPhenet_Training.ipynb: Train a new model and analyse the learning process from any trained model. 4_ImPhenet_Testing_d0.ipynb: Test any model for day 0. 5_ImPhenet_Testing_d7.ipynb: Test any model for day 7. Organoids_Unet: PhenotypePrediction: Preprocessing: Training: Utils: Visualisation: