Nference, Inc.

Anumana, Inc.

Tyler Wagner

Murali Aravamudan

Venkataramanan Soundararajan

Rakesh Barve

Shamim A Naqvi

Ajit Rajasekharan

Sankar Ardhanari

Karthik Murugadoss

Akash Anand

Katherine Carlson

Samir Awasthi

Corinne Carpenter

Ashim Prasad

Melwin Babu

Samuel J Asirvatham

Paul A Friedman

Suraj Kapa

Francisco Lopez-Jimenez

Tyler Feener

Jeyendran Balakrishnan

Bharathwaj Raghunathan

Vishal Jain

Eric Brine

Lorenzo Kogler Anele

Shimeng Chen

Rashik Shahjahan

Danylo Oliynyk

Ashwin Murali

Hilary M Dubrock

Enrique Garcia-Rivera

Itzhak Zachi Attia

Disclosed herein are methods for identifying and classifying relationships between entities. A method of identifying relationships includes receiving a first entity and a second entity; accessing a corpus; retrieving a plurality of sentences containing the first entity and the second entity from the corpus; identifying a plurality of relational phrases by extracting a relational phrase from each of the plurality of sentences; and identifying one or more relationships between the first entity and the second entity. A method of classifying relationships includes using a classification model.

Method and system for determining relationships between linguistic entities

System for observing medical conditions and methods used therein include a processor and a memory connected to the processor, wherein the memory contains instructions configuring the processor to receive, from a data repository, a plurality of reference electronic health records and a plurality of reference cardiac data elements, generate medical training data, train at least an observation machine learning model using the generated medical training data, receive a query pertaining to a subject, wherein the query includes at least a query cardiac data element and at least a query electronic health record, and output at least an observation outcome as a function of the query using the at least an observation machine learning model.

System and methods for observing medical conditions

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

Techniques are provided for computing with private healthcare data. The techniques include a method comprising constructing an isolated memory partition that forms a secure enclave and pre-provisioning software within the secure enclave. The pre-provisioned software is configured to receive at least one of input data or the instructions for the one or more application computing processes in an encrypted form; decrypt the at least one of input data or instructions using one or more cryptographic keys; execute the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generate a proof of execution that indicates that the one or more application computing processes operated on the received input data; encrypt the output data using the one or more cryptographic keys; and provide external access to the encrypted output data and the proof of execution.

Systems and methods for computing with private healthcare data

Grouping vectors describing functional interactions between compounds and reagents into clusters identifies groups of similar compounds, and may identify drug targets, pathways of action, deleterious toxicities, immune stimulation and evasion potential, or other information regarding interactions between compounds and reagents.

Systems and methods for drug clustering

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Boston, MA, United States of America

Tyler Wagner