Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: A data-driven integrative visualization system and a method for visualization and exploration of the multi-modal features of a cohort of samples, is disclosed Specifically, a method for providing an interactive computation and visualization front-end of a genomics platform for presenting the complex multiparametric and high dimensional, multi-omic data of a patient with respect to a cohort of samples, that assists the user in understanding the similarities and differences across individual or groups of samples, identify correlation among different features and improve treatment planning and long term patient care, is described. The method may include obtaining and inputting multi-omic data of a patient and/or cohorts, identifying multi-modal feature variations and their relationships, and displaying this information in an interactive circular format on a GUI, from which the user can access further information.

Abstract: The present disclosure relates to an augmented reality based user guidance system for multi-step medical procedures, the system comprising an augmented reality device (10, 30) comprising a display unit (14, 34) arranged to present artificial information that can be overlaid on an original scene, a sensor unit (18, 38), a processing unit (22, 42), at least one first marker (142, 144, 146, 148) that can be detected by the augmented reality device (10, 30), wherein the at least one first marker (142, 144, 146, 148) is associated with an object (132, 134, 136, 138) to be used in a defined step of the medical procedure, wherein the medical procedure comprises at least one step that requires a user action, wherein the augmented reality device (10, 30) is arranged to monitor a scene and to detect and track the at least one first marker (142, 144, 146, 148), provide user guidance to execute the medical procedure, detect whether user actions comply with the medical procedure, based on a detected state of the at least

Abstract: Through changes in lighting and audio solutions together with projections of images and/or animations that are initiated by the entrance of a person (professional or patient) in a medical environment, such as a radiology department, cardiology department, intensive care unit, etc., a certain ambience/atmosphere is created in this specific architectural context. This ambience can be a choice from certain predefined themes (e.g. animal drawings for children or nature images) or truly personal when personal content (e.g. images of family or vacation) is inserted in the system.