Abstract: Receiving a plurality of images of a first wall of the patient's heart, the plurality including a first image captured at a time ij and a second image captured at a time t2, determining, based on the plurality of images, a first characteristic of movement of at least a wall portion of the first wall during a time period spanning time t1 and time t2, the first characteristic of movement being determined by using one or more image processing techniques, and the first, characteristic of movement being based on at least one of: (i) a shape of the wall portion in the first image and a shape of the wall portion in the second image, and (ii) a location of the wall portion in the first image and a location of the wall portion in the second image: and outputting an indication of the first characteristic of movement.

Abstract: Receiving a plurality of images of a first wall of the patient's heart, the plurality including a first image captured at a time ij and a second image captured at a time t2, determining based on the plurality of images, a first characteristic of movement of at least a wall portion of the first wall during a time period spanning time t1 and time t2, the first characteristic of movement being determined by using one or more image processing techniques, and the first, characteristic of movement being based on at least one of: (i) a shape of the wall portion in the first image and a shape of the wall portion in the second image, and (ii) a location of the wall portion in the first image and a location of the wall portion in the second image: and outputting an indication of the first characteristic of movement.

Abstract: A trainable, adaptable system for analyzing functional or structural clinical data can be used to identify a given pathology based on functional data. The system includes a signal processor that receives functional data from a device monitoring a subject and normalizes the functional data over at least one cycle of functional data. The system also includes a neural network having a plurality of weights selected based on predetermined data and receiving and processing the normalized functional data based on the plurality of weights to generate at least one metric indicating a degree of relation between the normalized functional data to the predetermined data. A diagnostic interpretation module is included for receiving the at least one metric from the neural network and classifying the functional data as indicative of the given pathology or not indicative of the given pathology based on a comparison of the at least one metric to at least one probability distribution of a likelihood of the given pathology.

Abstract: An incentive program system and process for redeeming incentive program points. The system or process may be accomplished through a computer readable medium bearing instructions for administering the incentive program account. The system includes a database for storing points associated with a first incentive program account and a processor that, in response to a program participant's instructions, redeems a number of the points as either a discount for a transaction or for points in a second incentive program account. The process includes storing points associated with a first incentive program account; identifying either transactions available for the redemption of an incentive program discounter a second incentive program account to which said one or more points may be transferred; and either applying a discount to one or more of the transactions available for the redemption of an incentive program discount or transferring points to the second incentive program account.