公开(公告)号：US11967067B2

公开(公告)日：2024-04-23

申请号：US17319606

申请日：2021-05-13

Applicant: Merative US L.P.

Inventor： Shafiqul Abedin ,  Hongzhi Wang ,  Ehsan Dehghan Marvast ,  David James Beymer

IPC: G06T7/00 ,  G06F18/2433 ,  G06N3/045 ,  G06N3/08 ,  G06T7/11 ,  G06V10/34 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06F18/2433 ,  G06N3/045 ,  G06N3/08 ,  G06T7/11 ,  G06V10/34 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A candidate generator generates a set of candidate three-dimensional image patches from an input volume. A candidate classifier classifies the set of candidate three-dimensional image patches as containing or not containing disease. Classifying the set of candidate three-dimensional image patches comprises generating an attention mask for each given candidate three-dimensional image patch within the set of candidate three-dimensional image patches to form a set of attention masks, applying the set of attention masks to the set of candidate three-dimensional image patches to form a set of masked image patches, and classifying the set of masked image patches as containing or not containing the disease. The candidate classifier applies soft attention and hard attention to the three-dimensional image patches such that distinctive image regions are highlighted proportionally to their contribution to classification while completely removing image regions that may cause confusion.

公开(公告)号：US11963790B2

公开(公告)日：2024-04-23

申请号：US16952459

申请日：2020-11-19

Applicant: Merative US L.P.

Inventor： Arkadiusz Sitek ,  Mark D. Bronkalla ,  Larissa Christina Schudlo ,  Benedikt Graf ,  Yiting Xie

IPC: A61B5/00 ,  G06T7/00

CPC classification number: A61B5/4566 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30012

Abstract: An approach for a computer program to receive image data of a subject including at least a portion of a spine of the subject and a chronological age of the subject. The approach includes the computer program pre-processing the image data including at least a portion of a spine. The approach includes determining an apparent age of the spine or a portion of the spine of the subject using a trained artificial intelligence deep learning algorithm.

公开(公告)号：US11948694B2

公开(公告)日：2024-04-02

申请号：US17318027

申请日：2021-05-12

Applicant: Merative US L.P.

Inventor： Vishrawas Gopalakrishnan ,  Sayali Navalekar ,  James H. Kaufman ,  Simone Bianco ,  Kun Hu ,  Ajay Ashok Deshpande ,  Sarah Kefayati ,  Ujwal Reddy Moramganti ,  George Sirbu ,  Xuan Liu ,  Raman Srinivasan ,  Pan Ding

IPC: G06Q30/00 ,  G06N20/00 ,  G16H50/50 ,  G16H50/80

CPC classification number: G16H50/80 ,  G06N20/00 ,  G16H50/50

Abstract: Mechanisms are provided for compartmental epidemiological computer modeling based on mobility data. Machine learning training of an isolation rate prediction computer model is performed to generate a trained isolation rate prediction model that predicts an isolation rate of a biological population. Isolation data is received which comprises data indicating a measure of mobility of the biological population. The trained isolation rate prediction model is executed on input features extracted from the isolation data to generate a predicted isolation rate. A compartmental epidemiological computer model, comprising a plurality of compartments representing states of a population with regard to an infectious disease, is executed to simulate a progression of the infectious disease and flows of portions of the population from between compartments in the compartmental epidemiological computer model are controlled based on the predicted isolation rate.

公开(公告)号：US11900601B2

公开(公告)日：2024-02-13

申请号：US18170789

申请日：2023-02-17

Applicant: MERATIVE US L.P.

Inventor： Hans Harald Zachmann ,  Simona Rabinovici-Cohen ,  Shaked Brody

IPC: G06N5/04 ,  G06T7/00 ,  G06F9/455

CPC classification number: G06T7/0012 ,  G06F9/45558 ,  G06N5/04 ,  G06F2009/4557 ,  G06F2009/45575 ,  G06F2009/45583 ,  G06T2207/20081

Abstract: Methods and systems for processing medical images. One method includes, in response to startup of an application using an algorithm, creating a server process supporting a programming language associated with the algorithm and loading a plurality of deep learning models used by the algorithm into a memory of the server process to create in-memory models. The method also includes processing a first set of one or more medical images with the server process using the algorithm and at least one model selected from the in-memory models, maintaining the in-memory models in the memory of the server process after processing the first set of one or more medical images, and, in response to a request to process a second set of one or more medical images, processing the second set of one or more medical images using the algorithm and at least one of the in-memory models.

公开(公告)号：US11854197B2

公开(公告)日：2023-12-26

申请号：US17522196

申请日：2021-11-09

Applicant: Merative US L.P.

Inventor： Sun Young Park ,  Dustin Michael Sargent

IPC: G06T7/00 ,  G06T7/70 ,  G06N3/04 ,  A61B6/00 ,  A61B6/03

CPC classification number: G06T7/0012 ,  A61B6/032 ,  A61B6/504 ,  A61B6/5217 ,  G06N3/04 ,  G06T7/70 ,  G06T2207/10081 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30196

Abstract: A computer system identifies a medical condition in a patient. A trained machine learning image generator is used to generate a set of training images based on three-dimensional patient imaging data, wherein each training image is labeled with a projection angle of the corresponding two-dimensional projection. Using the set of training images, a machine learning image classifier model is trained to identify patient rotation angles in x-ray images. X-ray images are processed with the machine learning image classifier model to identify patient rotation angles. A machine learning medical condition classifier model is trained to identify a medical condition using the labeled x-ray images. The machine learning medical condition classifier model determines an indication of the medical condition in a patient's x-ray image. Embodiments of the present invention further include a method and program product for identifying a medical condition in a patient in substantially the same manner described above.

公开(公告)号：US11791024B2

公开(公告)日：2023-10-17

申请号：US15412895

申请日：2017-01-23

Applicant: Merative US L.P.

Inventor： Corville O. Allen

IPC: G16H10/60 ,  G06F21/62

CPC classification number: G16H10/60 ,  G06F21/6245

Abstract: A mechanism is provided in a data processing system to implement localized device specific limitations on access to patient medical information. An authorizing device receives a request from a requestor device via a dose proximity communication protocol requesting to access an electronic medical record (EMR) associated with a patient. The authorizing device receives user input via a user interface specifying conditions for permitting access to the EMR. The authorizing device transmits an access authorization request to a patient registry system requesting the patient registry system to provide access to the EMR associated with the patient in accordance with the conditions for permitting access specified by the user input. The patient registry system generates a temporary access data structure based on the specified conditions. The patient registry system processes a subsequent request from the requestor device to access the EMR in accordance with the temporary access data structure.

公开(公告)号：US11769571B2

公开(公告)日：2023-09-26

申请号：US17126798

申请日：2020-12-18

Applicant: Merative US L.P.

Inventor： James S. Cox

IPC: G16H10/20 ,  G06F16/2458 ,  G06F16/33 ,  G16H10/60 ,  G16H40/20 ,  G06F40/30 ,  G06F40/279 ,  G16H70/20

CPC classification number: G16H10/20 ,  G06F16/2477 ,  G06F16/3344 ,  G06F40/279 ,  G06F40/30 ,  G16H10/60 ,  G16H40/20 ,  G16H70/20

Abstract: Mechanisms are provided for determining values to associate with medical conditions of a patient. A patient assessment is received that comprises a natural language question and a corresponding answer, about a patient, provided in response to the question. Cognitive natural language processing is performed on the patient assessment to extract features from the natural language question and corresponding answer. The extracted features are evaluated within a context of a pre-existing electronic medical record of the patient. A value for a medical condition of the patient is determined based on results of the evaluation and stored in the electronic medical record for the patient.

公开(公告)号：US11763931B2

公开(公告)日：2023-09-19

申请号：US16377944

申请日：2019-04-08

Applicant: MERATIVE US L.P.

Inventor： Alexandros Karargyris ,  Chun Lok Wong ,  Joy Wu ,  Mehdi Moradi

IPC: G06T7/00 ,  G16H30/40 ,  G06N20/00 ,  G16H15/00 ,  G06F40/169 ,  G06F18/24 ,  G06F18/21 ,  G06F18/214 ,  G06V10/774 ,  G06V10/776 ,  G06F40/30

CPC classification number: G16H30/40 ,  G06F18/217 ,  G06F18/2148 ,  G06F18/24 ,  G06F40/169 ,  G06N20/00 ,  G06T7/0012 ,  G06V10/774 ,  G06V10/776 ,  G16H15/00 ,  G06F40/30 ,  G06T2207/10116 ,  G06T2207/20081

Abstract: Methods and systems are directed to training an artificial intelligence engine. One system includes an electronic processor configured obtain a set of reports corresponding to a set of medical images, determine a label for a finding of interest, and identify one or more ambiguous reports in the set of repots. Ambiguous reports do not include a positive label or a negative label for the finding of interest. The electronic processor is also configured to generate an annotation for each of the one or more ambiguous reports in the set of reports, and train the artificial intelligence engine using a training set including the annotation for each of the one or more ambiguous reports and non-ambiguous reports in the set of reports. A result of the training is generation of a classification model for the label for the finding of interest.

公开(公告)号：US11741694B2

公开(公告)日：2023-08-29

申请号：US16897225

申请日：2020-06-09

Applicant: MERATIVE US L.P.

Inventor： Larissa Christina Schudlo

IPC: G06V10/82 ,  G06T7/00 ,  G16H30/40 ,  G06N3/02 ,  G06F18/22 ,  G06F18/243 ,  G06V20/50 ,  G06T7/70

CPC classification number: G06V10/82 ,  G06F18/22 ,  G06F18/243 ,  G06N3/02 ,  G06T7/0012 ,  G06T7/70 ,  G06V20/50 ,  G16H30/40 ,  G06T2207/10116 ,  G06T2207/20084 ,  G06T2207/30012

Abstract: Methods and systems for detecting a vertebral fracture within an x-ray. One method includes receiving a chest x-ray image and identifying a plurality of vertebrae represented in the chest x-ray image. The method further includes extracting a plurality of image patches from the chest x-ray image, each image patch of the plurality of image patches including a portion of the chest x-ray image representing one of the plurality of vertebrae identified in the chest x-ray image. The method further includes sequencing the plurality of image patches into an ordered sequence of image patches, and assigning, with a deep learning model applied to the ordered sequence of image patches, a classification to each of the plurality of image patches indicating whether the image patch represents a fractured vertebra or an unfractured vertebra.

公开(公告)号：US20230186465A1

公开(公告)日：2023-06-15

申请号：US17948302

申请日：2022-09-20

Applicant: MERATIVE US L.P.

Inventor： Mark D. Bronkalla ,  Grant Covell ,  Amanda Long ,  David Richmond

IPC: G06T7/00 ,  A61B5/00 ,  G16H30/20 ,  G16H30/40 ,  G06N20/00

CPC classification number: G06T7/0012 ,  A61B5/0013 ,  G16H30/20 ,  G16H30/40 ,  G06N20/00 ,  G06N5/022

Abstract: Systems and methods for selectively processing image studies with an artificial intelligence system. One system includes an electronic processor configured to select an image study awaiting review and update a workflow status of the image study to a first status indicating that the image study has been claimed for review by the artificial intelligence system. The electronic processor is also configured to apply at least one of the plurality of rules to the image study to determine whether the image study is applicable for processing by the artificial intelligence system, and, in response to determining the image study is not applicable for processing by the artificial intelligence system based on the at least one of the plurality of rules, update the workflow status associated with the image study to a second status to make the image study available for claiming by a manual reviewer or another artificial intelligence system.