Abstract: The invention relates to inferring the state of a system of interest having a plurality of indicator values and possibly being heterogeneous in nature. A number of indicator values from a control state and from a comparison state are gathered. From these indicator values, classification power between the control and comparison states (measure of goodness) is computed. Difference values are computed for the indicator values from the system of interest based on the difference to the indicator values from control and comparison states. From a number of these indicators, composite indicators are formed, and composite measures of goodness and composite difference values are computed. A plurality of composite indicators may be formed at different levels. These indicators may be represented as a tree and grouped according to content, and at the same time they may be arranged according to the measure of goodness or some other value.

Abstract: The present disclosure relates to a method, apparatus, system and computer program for inferring a system state over time. Biomedical measurement data is obtained, wherein the data relate to at least one indicator of a system of interest and includes at least two indicator values being indicative of the state of the system of interest and the indicator values are measured at different time points. At least one measure of goodness for the indicator is formed by using values of the indicator of at least one control state and at least one comparison state. Difference values are formed for at least two indicator values with reference to the control and comparison states, and using the at least two difference values a change in value of said indicator is displayed with a progress indicator so that the change over time can be used in inferring the system state. The progress indicator has at least one dimension depending on the value of the at least one measure of goodness.

Abstract: The invention relates to inferring the state of a system of interest having a plurality of indicator values and possibly being heterogeneous in nature. A number of indicator values from a control state and from a comparison state are gathered. From these indicator values, classification power between the control and comparison states (measure of goodness) is computed. Difference values are computed for the indicator values from the system of interest based on the difference to the indicator values from control and comparison states. From a number of these indicators, composite indicators are formed, and composite measures of goodness and composite difference values are computed. A plurality of composite indicators may be formed at different levels. These indicators may be represented as a tree and grouped according to content, and at the same time they may be arranged according to the measure of goodness or some other value.

Abstract: The present disclosure relates to a method, apparatus, system and computer program for inferring a system state over time. Biomedical measurement data is obtained, wherein the data relate to at least one indicator of a system of interest and includes at least two indicator values being indicative of the state of the system of interest and the indicator values are measured at different time points. At least one measure of goodness for the indicator is formed by using values of the indicator of at least one control state and at least one comparison state. Difference values are formed for at least two indicator values with reference to the control and comparison states, and using the at least two difference values a change in value of said indicator is displayed with a progress indicator so that the change over time can be used in inferring the system state. The progress indicator has at least one dimension depending on the value of the at least one measure of goodness.

Abstract: The invention relates to inferring the state of a system of interest having a plurality of indicator values and possibly being heterogeneous in nature. A number of indicator values from a control state and from a comparison state are gathered. From these indicator values, classification power between the control and comparison states (measure of goodness) is computed. Difference values are computed for the indicator values from the system of interest based on the difference to the indicator values from control and comparison states. From a number of these indicators, composite indicators are formed, and composite measures of goodness and composite difference values are computed. A plurality of composite indicators may be formed at different levels. These indicators may be represented as a tree and grouped according to content, and at the same time they may be arranged according to the measure of goodness or some other value.