Application US20190183431

PREDICTING TRANSIENT ISCHEMIC EVENTS USING ECG DATA
[+] Show Details

US20190183431

1. A method for predicting an ischemic event, comprising: (5) (2)

receiving, by an ischemic event prediction neural network, a first neural network input, the first neural network input representing an electrocardiogram (ECG) recording of a subject mammal; and

processing, with the ischemic event prediction neural network, the first neural network input with a neural network to generate a prediction of an ischemic event for the subject mammal, the prediction indicating a likelihood that the subject mammal will experience the ischemic event within a pre-defined time interval from a time when the ECG recording was made.

2. The method of claim 1, wherein the ischemic event prediction neural network is trained on ECG training data that includes a plurality of ECG training samples, each ECG training sample including an ECG recording of a given mammal and a label indicating whether the given mammal is known to have experienced an ischemic event within the pre-defined time interval from the time when the ECG recording was made. (4) (0)

3. The method of claim 2, wherein the given mammals for particular ones of the ECG training samples are different from each other. (0)

4. The method of claim 2, wherein, for each of at least a subset of the ECG training samples, the label for the training sample or a second label for the training sample indicates an amount of time that elapsed between a time when the ECG recording for the training sample was made and a time when the given mammal for the training sample experienced an ischemic event. (0)

9. The method of claim 2, wherein at least two of the ECG training samples include ECG recordings of a same mammal taken at different times, the ECG training data further describing a change between the ECG recordings of the same mammal taken at different times. (0)

10. The method of claim 2, wherein the ECG recording of the subject mammal was recorded over a first time interval, and the method further comprises: (0) (2)

5. The method of claim 1, wherein the prediction of the ischemic event for the subject mammal further indicates an anticipated timing of the ischemic event. (0)

6. The method of claim 1, wherein the ischemic event is a transient ischemic attack (TIA). (0)

7. The method of claim 1, wherein the ischemic event is a stroke. (0)

8. The method of claim 1, wherein the pre-defined time interval is in the range of 1-10 years. (0)

11. A method for diagnosing an ischemic event for a subject mammal, comprising: (3) (2)

receiving, by an ischemic event detection neural network, a neural network input, the neural network input representing an electrocardiogram (ECG) recording of the subject mammal that was recorded over a period of time, the subject mammal having no appearance of the ischemic event over the period of time; and

processing, with the ischemic event detection neural network, the neural network input to determine a likelihood that the subject mammal experienced the ischemic event.

12. The method of claim 11, wherein the ischemic event detection neural network is trained on ECG training data that includes a plurality of ECG training samples, each ECG training sample including an ECG recording of a given mammal and a label indicating whether the given mammal is known to have experienced an ischemic event. (3) (0)

13. The method of claim 12, wherein the given mammals for particular ones of the ECG training samples are different from each other. (0)

14. The method of claim 12, wherein, for each of at least a subset of the ECG training samples, the label for the training sample or a second label for the training sample indicates an amount of time that elapsed between a time when the ECG recording for the training sample was made and a time when the given mammal for the training sample experienced an ischemic event. (0)

17. The method of claim 12, wherein the ECG recording of the subject mammal was recorded over a first time interval, and the method further comprises: (0) (2)

15. The method of claim 11, wherein the ischemic event is a transient ischemic attack (TIA). (0)

16. The method of claim 11, wherein the ischemic event is a stroke. (0)

18. A system for predicting an ischemic event, comprising: (1) (2)

one or more processors; and

one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause performance of operations comprising: receiving, by an ischemic event prediction neural network, a first neural network input, the first neural network input representing an electrocardiogram (ECG) recording of a subject mammal; and

processing, with the ischemic event prediction neural network, the first neural network input with a neural network to generate a prediction of an ischemic event for the subject mammal, the prediction indicating a likelihood that the subject mammal will experience a stroke within a pre-defined time interval from a time when the ECG recording was made.

19. The system of claim 18, wherein the ischemic event prediction neural network is trained on ECG training data that includes a plurality of ECG training samples, each ECG training sample including an ECG recording of a given mammal and a label indicating whether the given mammal is known to have experienced an ischemic event within the pre-defined time interval from the time when the ECG recording was made. (1) (0)

View Abstract and Specification Size

PDF with Images and Document Face >

Full Text Publication >

Application US20190183431

PREDICTING TRANSIENT ISCHEMIC EVENTS USING ECG DATA

Patent Matrix® Search