Abstract: A system and method for correcting colors in an image in order to identify pills. The system includes a surface that includes a background upon which pills are positioned and a border of known color adjacent to the background. The system also includes a digital camera and a processor. The processor is used to receive and process the image, use target objects on the surface to identify areas of the image that correspond to the known characteristics and features of the surface, perform image diagnostics to determine if the image can be used, and correct image color based on comparison of identified areas of the image that correspond with the known characteristics and features of the surface. Various graphical displays or cues can assist a user in obtaining a usable image.

Abstract: A system and method for identifying pills by determining a size and shape of each pill in a digital image. The system includes a background grid organized as a grid of alternating-colored shapes. The system also includes a digital camera, a processor and a memory. The processor is used to receive and process the digital image taken by the digital camera so as to determine contours for each pill in the image. The contour determination is refined and is used to determine size and shape information for each pill.

Abstract: A system and method for identifying pills by determining a size and shape of each pill in a digital image. The system includes a background grid organized as a grid of alternating-colored shapes. The system also includes a digital camera, a processor and a memory. The processor is used to receive and process the digital image taken by the digital camera so as to determine contours for each pill in the image. The contour determination is refined and is used to determine size and shape information for each pill.

Abstract: A system and method for correcting colors in an image in order to identify pills. The system includes a surface that includes a background upon which pills are positioned and a border of known color adjacent to the background. The system also includes a digital camera and a processor. The processor is used to receive and process the image, use target objects on the surface to identify areas of the image that correspond to the known characteristics and features of the surface, perform image diagnostics to determine if the image can be used, and correct image color based on comparison of identified areas of the image that correspond with the known characteristics and features of the surface. Various graphical displays or cues can assist a user in obtaining a usable image.

Abstract: A system and method for correcting colors in an image in order to identify pills. The system includes a surface that includes a background upon which pills are positioned and a border of known color adjacent to the background. The system also includes a digital camera and a processor. The processor is used to receive and process the image, use target objects on the surface to identify areas of the image that correspond to the known characteristics and features of the surface, perform image diagnostics to determine if the image can be used, and correct image color based on comparison of identified areas of the image that correspond with the known characteristics and features of the surface. Various graphical displays or cues can assist a user in obtaining a usable image.

Abstract: A system and method for identifying a pill by its imprint. A digital pill imprint image for the pill is obtained and compared with one or more composite imprint images in a database. Each of the composite imprint images is a composite of two or more digital pill imprint images of a single type of pill. The composite imprint images are formed by aligning and combining the two or more digital pill imprint images for each type of pill. A match score is determined as a result of the comparing of the digital pill imprint image with each of the composite imprint images. The match score represents a degree of overlap between the digital pill imprint image and each composite imprint image. The pill is identified based on the composite imprint image having the best match score.

Abstract: A system and method for correcting colors in an image in order to identify pills. The system includes a surface that includes a background upon which pills are positioned and a border of known color adjacent to the background. The system also includes a digital camera and a processor. The processor is used to receive and process the image, use target objects on the surface to identify areas of the image that correspond to the known characteristics and features of the surface, perform image diagnostics to determine if the image can be used, and correct image color based on comparison of identified areas of the image that correspond with the known characteristics and features of the surface. Various graphical displays or cues can assist a user in obtaining a usable image.

Abstract: A system and method for identifying pills by determining a size and shape of each pill in a digital image. The system includes a background grid organized as a grid of alternating-colored shapes. The system also includes a digital camera, a processor and a memory. The processor is used to receive and process the digital image taken by the digital camera so as to determine contours for each pill in the image. The contour determination is refined and is used to determine size and shape information for each pill.

Abstract: Disclosed is a method and system for analyzing patient hospitalization data to determine a Nosocomial Infection Marker (NIM), the method comprising receiving from a database hospitalization data associated with at least one patient, calculating from the hospitalization data the number of specimens with non-duplicate hospital isolates (SNDHI) markers, calculating from the hospitalization data antibiotic utilization criteria (AUC) markers, and determining the nosocomial infection marker (NIM) for each patient, based upon the calculated. SNDHI and AUC markers.

Abstract: Disclosed is a method and system for analyzing patient hospitalization data to determine a Nosocomial Infection Marker (NIM), the method comprising receiving from a database hospitalization data associated with at least one patient, calculating from the hospitalization data the number of specimens with non-duplicate hospital isolates (SNDHI) markers, calculating from the hospitalization data antibiotic utilization criteria (AUC) markers, and determining the nosocomial infection marker (NIM) for each patient, based upon the calculated SNDHI and AUC markers.

Abstract: Disclosed is a method and system for analyzing patient hospitalization data to determine a Nosocomial Infection Marker (NIM), the method comprising receiving from a database hospitalization data associated with at least one patient, calculating from the hospitalization data the number of specimens with non-duplicate hospital isolates (SNDHI) markers, calculating from the hospitalization data antibiotic utilization criteria (AUC) markers, and determining the nosocomial infection marker (NIM) for each patient, based upon the calculated SNDHI and AUC markers.

Abstract: Disclosed is a method and system for analyzing patient hospitalization data to determine a Nosocomial Infection Marker (NIM), the method comprising receiving from a database hospitalization data associated with at least one patient, calculating from the hospitalization data the number of specimens with non-duplicate hospital isolates (SNDHI) markers, calculating from the hospitalization data antibiotic utilization criteria (AUC) markers, and determining the nosocomial infection marker (NIM) for each patient, based upon the calculated SNDHI and AUC markers.

Abstract: A method for analyzing sets of temporal data using a computer is described. Each set of temporal data includes a plurality of records collected at a time unique to each such set and in which each record has a plurality of data items. The method includes the first step of creating data association rules for at least a plurality of sequential data sets wherein each association rule describes data items that are found together in some data records. An incidence proportion is then determined for each such association rule for each temporal data set and these incidence proportions are stored. The incidence proportions for each association rule are grouped into two aggregate proportions by a user defined window schedule that describes one or more pairs of a current window wc and a past window wp. The cumulative incidence proportions for each association rule for each past window wp are compared with the cumulative incidence proportion for the corresponding current window wc by a statistical test of two proportions.

Abstract: A method for analyzing sets of temporal data using a computer wherein each set of temporal data includes a plurality of records collected at a time unique to each such set and in which each record has a plurality of data items. The method includes the first step of creating data association rules for at least a plurality of sequential sets wherein each association rule represents data records having at least some common data items (100). A confidence factor is then determined for each such association rule and these confidence factors are stored in data partitions for the temporal data sets (102). The confidence factors for a selected data partition is then compared with the corresponding confidence factors of at least one other data partition (112), if available. When the confidence factor for the selected data partition varies from the corresponding confidence factor for the at least one other data partition exceeds a threshold value, an alert output signal is generated (114).