Nuance Communications, Inc.

Dictaphone Corporation.

Harry J Ogrinc

Robert G Titemore

Keith W Boone

Alwin B Carus

Roubik Manoukian

Jeffrey G Hopkins

Sean Gervais

Cameron Fordyce

Sunitha Chaparala

Melissa MacPherson

Brian Wilson

Stefaan Heyvaert

Tom Deplonty

Ray Rankins

Don Fonza

David Speth

In a method for validating data, a text of a document is received. At least one fact is extracted from the text. At least one expert refinement is merged with the at least one fact to create at least one modified fact. The at least one modified fact is provided for a review. An expert refinement to the at least one modified fact is captured in response to the review. A superset document based on the at least one pre-existing refinement and the expert refinement is stored.

Method, system, and apparatus for validation

A system and method may be disclosed for facilitating the creation or modification of a document by providing a mechanism for locating relevant data from external sources and organizing and incorporating some or all of said data into the document. In the method for reusing data, there may be a set of documents that may be queried, where each document may be divided into a plurality of sections. A plurality of section text groups may be formed based on the set of documents, where each section text group may be associated with a respective section from the plurality of sections and each section group includes a plurality of items. Each item may be associated with a respective section from each document of the set of documents. A selected item within a selected section text group may be focused. The selected item may be extracted to a current document. The current document may be exported to a host application.

Method, system, and computer-readable medium for creating a new electronic document from an existing electronic document

A computer implemented method for generating a report that includes latent information, comprising receiving an input data stream that includes latent information, performing one of normalization, validation, and extraction of the input data stream, processing the input data stream to identify latent information within the data stream that is required for generation of a particular report, wherein said processing of the input data stream to identify latent information comprises of identifying a relevant portion of the input data stream, bounding the relevant portion of the input data stream, classifying and normalizing the bounded data, activating a relevant report template based on said identified latent information, populating said template with template-specified data, and processing the template-specified data to generate a report.

Categorization of information using natural language processing and predefined templates

Method, system and apparatus for data reuse

Method, system, and apparatus for data reuse

Methods and systems for classifying and normalizing information using a combination of traditional data input methods, natural language processing, and predetermined templates are disclosed. One method may include activating a template. Based on this template, template-specific data may also be retrieved. After receiving both an input stream of data and the template-specific data, this information may be processed to generate a report based on the input data and the template specific data. In an alternative embodiment of the invention, templates may include, for example, medical billing codes from a number of different billing code classifications for the generation of patient bills. Alternatively, a method may include receiving an input stream of data and processing the input stream of data. A determination may be made as to whether or not the input stream of data includes latent information. If the data includes latent information, a template associated with latent information may be activated.

The invention includes a medical document handling system and method and automated coding systems and methods for assigning predetermined medical codes to medical documents based on the documents' contents. The invention functions by analyzing electronic medical records and extracting medical information using natural language processing and machine learning. The system collects and amalgamates medical documentation in various formats from multiple sources and locations, normalizes the information, analyzes the information, recognizes information indicating contents corresponding to classification codes, assigns classification codes, and presents information in context correlated to medical records for billing and other purposes.

Systems and methods for coding information

Growing community of inventors

Westwood, MA, United States of America

Harry J Ogrinc