Nference, Inc.

Akash Anand

Rakesh Barve

Murali Aravamudan

Venkataramanan Soundararajan

Shamim A Naqvi

Ajit Rajasekharan

Sankar Ardhanari

Tyler Wagner

Karthik Murugadoss

Samir Awasthi

Arjun Puranik

Praveen Kumar

Aravind Srinivasan

Jatin Kumar Tomar

Purushottam Sinha

Shashank Jaiswal

Anurag Vij

A system for retrieving patient information using large language models including a computing device configured to receive a natural language query as a function of a user input, input the natural language query into a large language model communicatively connected to the least a processor, receive a computer language query comprising a plurality of nodes from the large language model, map the plurality of nodes to one or more entries in a patient database, receive a database response from the patient database as a function of the mapping, generate a final database query as a function of the database response. query the patient database using the final database query, receive a user response as a function of the final database query, and transmit the user response to a graphical user interface as a function of the final database query.

Systems and methods for retrieving patient information using large language models

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

An apparatus for generating annotations for electronic records is disclosed. The apparatus includes a processor and a memory containing instructions configuring the processor to receive unstructured data for a plurality of electronic records and generate a plurality of machine learning models (MLMs), wherein each MLM of the plurality of MLMs is trained using a machine learning algorithm. The processor is further configured to generate at least one annotation for the unstructured data using each MLM of the plurality of MLM and structure the unstructured data as structured data as a function of the generated annotations.

Apparatus and method for generating annotations for electronic records

A method and system is provided for mapping a term to a vector representation in a semantic space. Provided techniques allow for efficient and accurate determination of vector representations for query terms that are terms of emerging interest or are otherwise not included in a set of terms for which vector representations are pre-calculated.

Systems and methods for mapping a term to a vector representation in a semantic space

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Bengaluru, India

Akash Anand