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AI Biotech/Diagnostics: Other Innovation
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Application US20190183431
Published 2019-06-20
Predicting Transient Ischemic Events Using Ecg Data
Apparatuses and methods are provided to predict or diagnose an ischemic event, such as a stroke or a transient ischemic attack (TIA). A machine-learning model such as a neural network is generated that allows for recognition of an ECG consistent with an ischemic event. A system is trained and used to process a recording of ECG data from a patient to generate a prediction indicating a likelihood that the patient will experience a stroke. In other examples, a system is trained and used to process a recording of ECG data from a patient and detect an ischemic event for the patient who did not appear to have such an ischemic event.
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- 1. A method for predicting an ischemic event, 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 the ischemic event within a pre-defined time interval from a time when the ECG recording was made.
- 11. A method for diagnosing an ischemic event for a subject mammal, comprising:
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.
- 18. A system for predicting an ischemic event, comprising:
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.
