Abstract: A computer system generates a clinical summary for a patient based on machine learning. One or more templates are generated, each indicating medical information for a corresponding clinical summary with respect to a medical condition of a patient. Preferences for medical information for each corresponding clinical summary are learned based on a history of desired medical information for clinical summaries for the medical condition. The learned preferences are applied to the one or more templates. A clinical summary is generated with respect to the medical condition of the patient based on the one or more templates with the learned preferences. Embodiments of the present invention further include a method and program product for generating a clinical summary for a patient based on machine learning in substantially the same manner described above.

Abstract: Methods, systems, and computer readable media are provided for processing medical images. One or more prior medical images are aligned with a current medical image. Image subtraction between the current medical image and the one or more prior medical images is performed to produce one or more difference images. The one or more difference images are applied to a machine learning model to determine a presence or an absence of a medical condition.

Abstract: A computer system generates a clinical summary for a patient based on machine learning. One or more templates are generated, each indicating medical information for a corresponding clinical summary with respect to a medical condition of a patient. Preferences for medical information for each corresponding clinical summary are learned based on a history of desired medical information for clinical summaries for the medical condition. The learned preferences are applied to the one or more templates. A clinical summary is generated with respect to the medical condition of the patient based on the one or more templates with the learned preferences. Embodiments of the present invention further include a method and program product for generating a clinical summary for a patient based on machine learning in substantially the same manner described above.

Abstract: Methods, systems, and computer readable media are provided for processing medical images. One or more prior medical images are aligned with a current medical image. Image subtraction between the current medical image and the one or more prior medical images is performed to produce one or more difference images. The one or more difference images are applied to a machine learning model to determine a presence or an absence of a medical condition.

Abstract: The present invention, in one form, is a system for simultaneously displaying an image object generated from an imaging system and a graphical object so that each object is fully visible. More specifically, after generating the image object, a graphical object is generated having a partial opacity value. The image object and graphical object are then sorted and combined so that the graphical object is in front of, or overlays, the image object without blocking or obscuring the information included in the image object. Particularly, a final image is generated by combining a destination value for components of each object.

Abstract: A graphic workstation receives digitized medical images and the user creates textual information that is to be displayed on the images. The text along with associated properties are packaged as a data structure along with a set of properties, and the data structure is passed through a pipeline having a series of formatters. The formatters are easily configured by the user to modify the properties of the text data structures as they flow through the pipeline prior to being rendered on a display.