Abstract: In pattern discovery visual analytics, a patient data table (14) is generated that tabulates, for each patient, attribute values for a set of attributes. A positive or negative prediction is generated for each patient for a target value of a target attribute using a prediction pattern (20) of attribute values for w attributes (22). The prediction is positive if at least a threshold fraction (26) of the w attributes of the patient match the prediction pattern, is negative otherwise. Patients are grouped into a selected proportion of a confusion matrix (30) in accord with the positive or negative predictions and actual values of the target attribute T in the patient data table. A display component (4) displays a representation (42) of patient statistics for the selected proportion of the confusion matrix on a per-attribute basis for attributes of the w attributes. A patient cohort (44) is identified using the representation.

Abstract: The present invention generally relates to time allocation of a clinical process. It is proposed in the present invention to introduce statistical significance as an indicator of the real improvement of activities in the modified time allocation against the original time allocation to achieve a statistically meaningful time allocation.

Abstract: In pattern discovery visual analytics, a patient data table (14) is generated that tabulates, for each patient, attribute values for a set of attributes. A positive or negative prediction is generated for each patient for a target value of a target attribute using a prediction pattern (20) of attribute values for w attributes (22). The prediction is positive if at least a threshold fraction (26) of the w attributes of the patient match the prediction pattern, is negative otherwise. Patients are grouped into a selected proportion of a confusion matrix (30) in accord with the positive or negative predictions and actual values of the target attribute T in the patient data table. A display component (4) displays a representation (42) of patient statistics for the selected proportion of the confusion matrix on a per-attribute basis for attributes of the w attributes. A patient cohort (44) is identified using the representation.

Abstract: A portable computing device (212) includes an analog clock device (244), a shift timer device (230), and a display device (214). The analog clock device (244) is configured to generate an analog clock face including concentric circles and task icons, each concentric circle including arranged icons of a selected task type. The shift timer device (230) is configured to identify a selected time window on the analog clock face. The display device (214) is configured to display the generated analog clock face. A display device 303 may display neonatal intensive care unit related information. Caregiver information, including information relating to a caregiver workload, may be displayed. Patient information, including vital sign information and event information, may be displayed.

Abstract: Systems and methods for providing an indication of the relative condition of neonatal subjects. Test datasets are obtained which describe monitored vital functions of a test subject. The test dataset is compared with one or more previously obtained model datasets describing model vital functions. Based on the comparison of the test datasets with the model datasets of vital functions a progress prediction for the development of the vital functions of the test subject may be determined. An indication of the progress prediction for the development of vital functions may be presented to a user to assist in the future handling of the test subject.

Abstract: A method, gesture input devices and a computer program product are provided for gesture enabled simultaneous selection of range and value. A user makes a gesture with two fingers (210, 220) to select a range of values (e.g. one of a range of seconds, minutes or hours) and select a value from this selected range of values (e.g. if the selected range of values is hours, a value between 00-23 hours). The gesture is captured using a camera based input device or a touch input device, which detects two user input contact points (230, 240). The distance (250) between these two user input contact points (230, 240) determines the selected range of values. The selection of the value from this selected range of values is determined by an angle (280) between two imaginary lines (250, 270). The first imaginary line (250) is the line between the first (230) and second (240) user input contact point.