Abstract: The invention discloses a system configured for assessing performance data, the system comprising a memory comprising instruction data representing a set of instructions; and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to: acquire a plurality of performance data records associated with a performance indicator; classify each performance data record according to the performance indicator; identify a plurality of variables in the performance data records that contribute to the classifications; determine, based on the plurality of variables, a plurality of observations relating to the performance indicator and at least one variable of the plurality of variables; and deliver the plurality of observations for presentation to a user. A method is also disclosed.

Abstract: A data processing system and related method. The system comprises an input interface for receiving data to be data-mined for a target. A categorizer configured to compute one or more category operators suitable to categorize said data. The computing by the categorizer of the category operators includes computing a metric. The system further includes an output interface for outputting the so computed one or more category operators.

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: In a patient record identification apparatus, at least one query value relating to at least one medical condition is input (210). Patient records are received (220) from a patient database. Each patient record includes at least one attribute value relating to the at least one medical condition, and each patient record includes information relating to an outcome of the at least one medical condition. A first set of patient records is determined (230) based on a similarity between the at least one query value input by the user and the at least one attribute value for the patient records. The first set of patient records is separated (240) into patient records relating to a positive outcome and into patient records relating to a negative outcome.

Abstract: The present invention relates to an apparatus (10) for patient data availability analysis. It is described to specify (210) a plurality of models, wherein each model provides output as a function of model variables. At least some model variables are defined (220) for the plurality of models. Source variables are specified (230), wherein a model variable can be derived from one or more source variables. At least one data source is specified (240). A plurality of data records are received (250) from the at least one data source, wherein each data record comprises at least one attribute. A set of available data records are determined (260) for each model from the plurality of data records, the determination for a model comprising utilizing the model variables for that model, the associated source variables and the at least one attribute for the plurality of data records.

Abstract: The invention discloses a system configured for assessing performance data, the system comprising a memory comprising instruction data representing a set of instructions; and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to: acquire a plurality of performance data records associated with a performance indicator; classify each performance data record according to the performance indicator; identify a plurality of variables in the performance data records that contribute to the classifications; determine, based on the plurality of variables, a plurality of observations relating to the performance indicator and at least one variable of the plurality of variables; and deliver the plurality of observations for presentation to a user. A method is also disclosed.

Abstract: An electronic clinical decision support (CDS) device executes (54) clinical decision rules (8) using a computer (10, 12) to generate predicted values of clinical conclusions (58) for a current patient based on values for the current patient of preconditions of the clinical decision rules (52). The rules are also executed (36) to generate predicted values of the clinical conclusions (38) for past patients based on values for the past patients of the preconditions (32) retrieved from an Electronic Medical Record (EMR) (20). Rule summary scores (42) are generated (40) based on comparisons of “ground truth” values of the clinical conclusions (34) for the past patients retrieved from the EMR with the predicted values of the clinical conclusions for the past patients. A display (14) shows the predicted values of the clinical conclusions and the corresponding applied rules for the current patient ranked at least in part by the rule summary scores.

Abstract: Presented are concepts for providing subject-specific information. One such concept comprises obtaining a first knowledge model, the first knowledge model comprising a plurality of clinical data elements for a population of subjects and relationship information representing one or more relationships between the clinical data elements. Also obtained is historical data relating to a sub-population of the population of subjects, the historical data relating to previously-obtained clinical data elements and relationship information for the sub-population. A second knowledge model is generated based on the first knowledge model and the historical data. A subject-specific model is generated based on the second knowledge model and subject-specific data relating to a subject.

Abstract: The present invention relates to an apparatus (10) for patient record identification. It is described to input (210) at least one query value relating to at least one medical condition. Patient records are received (220) from a patient database. Each patient record comprises at least one attribute value relating to the at least one medical condition, and each patient record comprises information relating to an outcome of the at least one medical condition. A first set of patient records is determined (230) based on a similarity between the at least one query value input by the user and the at least one attribute value for the patient records. The first set of patient records is separated (240) into patient records relating to a positive outcome for the at least one medical condition and into patient records relating to a negative outcome for the at least one medical condition.

Abstract: There is provided a computer-implemented method for generating a care plan for a subject. A plurality of care plans stored in one or more databases are accessed (202). The plurality of care plans are grouped into a plurality of care plan categories based on a similarity measure between one or more attributes of the plurality of care plans. Each of the plurality of care plans is associated with a reference subject. A care plan category for the subject is identified from the plurality of care plan categories using a trained classifier (204). A care plan for the subject is generated (206) based on the one or more care plans that are grouped into the identified care plan category, by maximizing a similarity measure between one or more attributes of the subject and one or more corresponding attributes of the reference subjects.

Abstract: A data processing system and related method. The system comprises an input interface for receiving data to be data-mined for a target. A categorizer configured to compute one or more category operators suitable to categorize said data. The computing by the categorizer of the category operators includes computing a metric. The system further includes an output interface for outputting the so computed one or more category operators.

Abstract: Presented is a concept for discovering a pattern in a dataset, where the dataset comprises a plurality of records, each record associated with a plurality of attribute values. The concept comprises defining a target attribute value and ascertaining a set of candidate attribute values based on the target attribute value. The set of candidate attribute values may be considered as a potential pattern in the dataset. For each record, the target attribute values and candidate attribute values are compared to the attribute values of that record so as to identify matching attribute values. A matching indicator is generated for each record based on a comparison between the number of matching attributes values and a matching threshold value, such that the matching indicator indicates a degree of similarity between the attribute values of the record and the set of candidate attribute values and the target attribute value.

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 accessing data selected by a user based on correlation analysis. It is proposed in the present invention to introduce attribute value normalization and a hierarchical data analysis based on mutual correlations between attributes. Normalization of scale values of attributes to nominal values provides a basis for the hypothesis of correlations between attributes, thus scientifically justifying further observation and comparison. Multiple layer hierarchical investigation enables not only analysis on the level of attributes but also of related data, which provides a more detailed observation.

Abstract: First and second components of the present invention, in combination, provide a customer interface for initiating a trade transaction and provides for the secure viewing of the status of the transaction. A third component assists in the automatic generation and verification of the voluminous and detailed documents required to support a trade transaction. The third component additionally tracks and assists in the management of the seller's manufacturing and shipment of the goods that form the basis of the trade transaction. A fourth component automatically generates a Letter of Credit from a Purchase Order and performs a reconciliation function on payments made pursuant to Letters of Credit or open Accounts.

Abstract: First and second components of the present invention, in combination, provide a customer interface for initiating a trade transaction and provides for the secure viewing of the status of the transaction. A third component assists in the automatic generation and verification of the voluminous and detailed documents required to support a trade transaction. The third component additionally tracks and assists in the management of the seller's manufacturing and shipment of the goods that form the basis of the trade transaction. A fourth component automatically generates a Letter of Credit from a Purchase Order and performs a reconciliation function on payments made pursuant to Letters of Credit or open Accounts.

Abstract: First and second components of the present invention, in combination, provide a customer interface for initiating a trade transaction and provides for the secure viewing of the status of the transaction. A third component assists in the automatic generation and verification of the voluminous and detailed documents required to support a trade transaction. The third component additionally tracks and assists in the management of the seller's manufacturing and shipment of the goods that form the basis of the trade transaction. A fourth component automatically generates a Letter of Credit from a Purchase Order and performs a reconciliation function on payments made pursuant to Letters of Credit or open Accounts.

Abstract: First and second components of the present invention, in combination, provide a customer interface for initiating a trade transaction and provides for the secure viewing of the status of the transaction. A third component assists in the automatic generation and verification of the voluminous and detailed documents required to support a trade transaction. The third component additionally tracks and assists in the management of the seller's manufacturing and shipment of the goods that form the basis of the trade transaction. A fourth component automatically generates a Letter of Credit from a Purchase Order and performs a reconciliation function on payments made pursuant to Letters of Credit or open Accounts.