Abstract: Apparatuses, methods, and systems for automated, non-invasive evaluation of cell activity are provided. In one embodiment, an apparatus includes a hypothesis selection module configured to select a hypothesis from a plurality of hypotheses characterizing one or more cells shown in an image. Each of the plurality of hypotheses includes an inferred characteristic of the one or more cells based on geometric features of the one or more cells shown in the image. The hypothesis selection module is implemented in at least one of a memory or a processing device.

Abstract: Apparatuses, methods, and systems for automated cell classification, embryo ranking, and/or embryo categorization are provided. An apparatus includes a classification module configured to apply classifiers to images of one or more cells to determine, for each image, a classification probability associated with each classifier. Each classifier is associated with a distinct first number of cells, and is configured to determine the classification probability for each image based on cell features including one or more machine learned cell features. The classification probability indicates an estimated likelihood that the distinct first number of cells is shown in each image. The classification module is further configured to classify each image as showing a second number of cells based on the distinct first number of cells and the classification probabilities associated therewith. The classification module is implemented in at least one of a memory or a processing device.

Abstract: A method for predicting and quantifying risk in information technology (IT) service contracts includes comparing features of a new IT service contract with similar features from one or more previous IT service contracts selected from a plurality of previous IT service contracts to calculate a similarity value between each pair of the new IT service contract and one of the one or more previous IT service contracts, aggregating the similarity values, and using the aggregated similarity values with a prediction model to predict risk factors affecting the new IT service contract and to quantify an impact of each predicted risk factor on an expected gross profit margin.

Abstract: A method for predicting and quantifying risk in information technology (IT) service contracts includes comparing features of a new IT service contract with similar features from one or more previous IT service contracts selected from a plurality of previous IT service contracts to calculate a similarity value between each pair of the new IT service contract and one of the one or more previous IT service contracts, aggregating the similarity values, and using the aggregated similarity values with a prediction model to predict risk factors affecting the new IT service contract and to quantify an impact of each predicted risk factor on an expected gross profit margin.