Abstract: A computer system automatically converts a set of training images of cells (e.g., oocytes or pronuclear embryos) and related outcome metadata into a description document by extracting features (e.g., cytoplasm features) from the pixel values of the training images that describe the cells and associating the extracted features with the outcome metadata. Based on the description document, the system automatically computes a decision model that can be used to predict outcomes of new cells. To predict outcomes of new cells, a computer system automatically extracts features from images that describe the new cells and predicts one or more outcomes by applying the decision model. The features extracted from the images that describe the new cells correspond to features selected for inclusion in the decision model, and are calculated in the same way as the corresponding features extracted from the training images.

Abstract: A computer system is configured to support clinical decision-making associated with patient treatment during the course of, e.g., an ovarian stimulation cycle. The system includes one or more computing devices programmed to receive patient training data; create decision model(s) using the patient training data; receive patient input data for at least one patient; provide the patient input data as input to the decision model(s); obtain output from the decision model(s); and generate recommendations for patient treatment for presentation via a user interface based on the output of the decision model. The decision model(s) may be created using random decision forests. The output from the decision model(s) may include confidence percentages for potential outcomes. The recommendations may be generated based on the confidence percentages.

Abstract: A computer system automatically converts a set of training images of cells (e.g., oocytes or pronuclear embryos) and related outcome metadata into a description document by extracting features (e.g., cytoplasm features) from the pixel values of the training images that describe the cells and associating the extracted features with the outcome metadata. Based on the description document, the system automatically computes a decision model that can be used to predict outcomes of new cells. To predict outcomes of new cells, a computer system automatically extracts features from images that describe the new cells and predicts one or more outcomes by applying the decision model. The features extracted from the images that describe the new cells correspond to features selected for inclusion in the decision model, and are calculated in the same way as the corresponding features extracted from the training images.