Abstract: In some embodiments, a current state of a medical condition or a progression of the medical condition is predicted by processing one or more digital pathology images and expression levels of genes using a machine-learning model. In some embodiments, one or more predicted gene-expression levels are generated by processing a data set corresponding to one or more digital pathology images using a machine-learning model. In some embodiments, one or more predicted digital pathology metrics are generated by processing a data set that corresponds to expression levels of a set of genes using a machine-learning model.

Abstract: The mobile device receives a prediction result via a digital cellular mobile telecommunication network. The prediction result has been generated by a program logic using a biomedical model. The prediction result includes a prediction score, a first confidence interval of prediction scores known to have a percentage of false negative predictions below a predefined FN-percentage threshold and a second confidence interval of score values known to have a percentage of false positive predictions below a predefined FP-percentage threshold. The mobile device displays an analog scale icon including a background area having the prediction score, an analog scale representing the score range; a pointer; a first sub-range indicator indicating the size and position of the first confidence interval; and a second sub-range indicator indicating the size and position of the second confidence interval within the score range.