Anumana, Inc.

Katherine Carlson

Murali Aravamudan

Venkataramanan Soundararajan

Tyler Wagner

Corinne Carpenter

Rakesh Barve

Ashim Prasad

Melwin Babu

Samuel J Asirvatham

Paul A Friedman

Suraj Kapa

Francisco Lopez-Jimenez

Samir Awasthi

Hilary M Dubrock

Itzhak Zachi Attia

Provided herein are methods, systems, and computer program products for the detection of pulmonary hypertension comprising receiving voltage-time data of a plurality of leads of an electrocardiograph of a subject; generating a feature vector from the voltage-time data; providing the feature vector to a pretrained learning system; and receiving from the pretrained learning system an indication of the presence or absence of pulmonary hypertension in the subject.

Noninvasive methods for detection of pulmonary hypertension

Disclosed systems, methods, and computer readable media can diagnose a health condition based on patient time series data. For example, a method for diagnosing a health condition based on patient time series data includes identifying a training set of health records comprising a first set of patient time series data, training a neural network using the training set of health records, and executing the trained neural network model to diagnose a health condition based on a second set of patient time series data. In further examples, the first set of patient time series data and the second set of patient time series data can each comprise electrocardiogram data and the health condition can comprise pulmonary hypertension.

Systems and methods for diagnosing a health condition based on patient time series data

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Cambridge, MA, United States of America

Katherine Carlson