公开(公告)号：US20220277576A1

公开(公告)日：2022-09-01

申请号：US17746233

申请日：2022-05-17

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Barry Ahrens

IPC: G06V30/413 ,  G06F40/279 ,  G06F40/30 ,  G06V30/414

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.

公开(公告)号：US20230394242A1

公开(公告)日：2023-12-07

申请号：US18236111

申请日：2023-08-21

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Naouel Baili Ben Abdallah ,  Barry Ahrens

IPC: G06F40/30 ,  G16H10/20 ,  G06N3/04 ,  G06N3/08 ,  G06F40/253 ,  G06F40/284 ,  G06F40/295

CPC classification number: G06F40/30 ,  G16H10/20 ,  G06N3/04 ,  G06N3/08 ,  G06F40/253 ,  G06F40/284 ,  G06F40/295

Abstract: Documents in source natural languages are translated into target natural languages using a computer-implemented translation that is configured to operate within the domain of the subject matter of the documents that imposes specialized requirements for translation and readability. Subject matter specific documents typically include domain-specific terminology, are subject to various regulatory guidelines, and have different readability requirements depending on the intended reader. The computer-implemented translation applies machine-learning techniques that deconstruct elements of the subject matter specific document into a standard data structure and perform pre-processing steps to tokenize digitized document text to identify the correct sentence structure and syntax for the target natural language to optimize translation by, e.g., a neural machine translation engine. The text segments that are input into the neural machine translation engine are generated to be semantically meaningful in the target natural language to thereby enhance the understanding of the neural machine translation engine.

公开(公告)号：US20230317261A1

公开(公告)日：2023-10-05

申请号：US18131256

申请日：2023-04-05

Applicant: IQVIA Inc.

Inventor： Olaf Vanggaard ,  Olatz Fruniz ,  Barry Ahrens ,  Melanie Brewer ,  Gary Shorter

IPC: G16H40/20 ,  G06Q30/018

CPC classification number: G16H40/20 ,  G06Q30/018

Abstract: A computer-implemented method includes receiving, by a machine learning model, a question associated with healthcare compliance from a user; identifying, by the machine learning model, a healthcare compliance regulation document associated with the question and one or more healthcare compliance requirements corresponding to the healthcare compliance regulation document; and recommending, by the machine learning model, a decision satisfying the one or more healthcare compliance requirements to the user.

公开(公告)号：US11734514B1

公开(公告)日：2023-08-22

申请号：US17098812

申请日：2020-11-16

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Naouel Baili Ben Abdallah ,  Barry Ahrens

IPC: G06F40/00 ,  G06F40/30 ,  G16H10/20 ,  G06N3/04 ,  G06F40/295 ,  G06F40/253 ,  G06F40/284 ,  G06N3/08

CPC classification number: G06F40/30 ,  G06F40/253 ,  G06F40/284 ,  G06F40/295 ,  G06N3/04 ,  G06N3/08 ,  G16H10/20

Abstract: Documents in source natural languages are translated into target natural languages using a computer-implemented translation that is configured to operate within the domain of the subject matter of the documents that imposes specialized requirements for translation and readability. Subject matter specific documents typically include domain-specific terminology, are subject to various regulatory guidelines, and have different readability requirements depending on the intended reader. The computer-implemented translation applies machine-learning techniques that deconstruct elements of the subject matter specific document into a standard data structure and perform pre-processing steps to tokenize digitized document text to identify the correct sentence structure and syntax for the target natural language to optimize translation by, e.g., a neural machine translation engine. The text segments that are input into the neural machine translation engine are generated to be semantically meaningful in the target natural language to thereby enhance the understanding of the neural machine translation engine.

公开(公告)号：US20210034855A1

公开(公告)日：2021-02-04

申请号：US17070533

申请日：2020-10-14

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Barry Ahrens

IPC: G06K9/00 ,  G06F40/279 ,  G06F40/30

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.

公开(公告)号：US11869263B2

公开(公告)日：2024-01-09

申请号：US17746233

申请日：2022-05-17

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Barry Ahrens

IPC: G06V30/412 ,  G06F40/279 ,  G06F40/30 ,  G06V30/413 ,  G06V30/414 ,  G06V30/196 ,  G06V30/10 ,  G06V30/32

CPC classification number: G06V30/412 ,  G06F40/279 ,  G06F40/30 ,  G06V30/1983 ,  G06V30/413 ,  G06V30/414 ,  G06V30/10 ,  G06V30/32 ,  G06V2201/09 ,  G06V2201/10

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.

公开(公告)号：US11373423B2

公开(公告)日：2022-06-28

申请号：US17070533

申请日：2020-10-14

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Barry Ahrens

IPC: G06V30/413 ,  G06F40/279 ,  G06F40/30 ,  G06V30/414

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.

公开(公告)号：US20200279108A1

公开(公告)日：2020-09-03

申请号：US16289729

申请日：2019-03-01

Applicant: IQVIA Inc.

Inventor： Gary Shorter ,  Barry Ahrens

IPC: G06K9/00 ,  G06F17/27

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.