Patent ID: 11972869
Assignee: ANUMANA, INC.
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC G

Claim 10:
11. A system for diagnosing a health condition based on patient time series data, wherein the system comprises:
a non-transitory memory; and
one or more hardware processors configured to read instructions from the non-transitory that, when executed, cause the one or more hardware processors to perform operations comprising:
receive patient time series data, wherein the patient time series data comprises an electrocardiogram (ECG) waveform;
identify a training set of health records, wherein:
the training set of health records comprises health records of patients who have been diagnosed with a health condition of interest and training data including ECG waveforms of the patients correlated to the health condition of interest; and
identifying the training set of health records comprises identifying one or more cohorts of the patients;

train a plurality of neural network models for each cohort of the patients using the training set of health records;
select one or more highest performing models from the plurality of trained neural network models;
execute the one or more highest performing models as a function of the patient time series data, wherein executing the one or more highest performing models comprises:
preprocessing the time series data, wherein preprocessing the time series data comprises:
extracting one or more discrete metrics as a function of the time series data, wherein the one or more discrete metrics comprises an interval of an ECG waveform; and

predict a health condition as a function of the patient time series data, the interval o the ECG wave form, and the one or more highest performing models.