公开(公告)号：US20240070440A1

公开(公告)日：2024-02-29

申请号：US18280160

申请日：2022-02-23

Applicant: Bayer Aktiengesellschaft

Inventor： Johannes HOEHNE ,  Steffen VOGLER ,  Matthias LENGA

IPC: G06N3/0455

CPC classification number: G06N3/0455

Abstract: Systems, methods, and computer programs disclosed herein relate to training a machine learning model to generate multimodal representations of objects, and to the use of said representations for predictive purposes.

公开(公告)号：US20240347206A1

公开(公告)日：2024-10-17

申请号：US18602895

申请日：2024-03-12

Applicant: Bayer Aktiengesellschaft

Inventor： Steffen VOGLER ,  Johannes Hohne ,  Matthias Lenga

IPC: G16H50/30 ,  G16H50/80

CPC classification number: G16H50/30 ,  G16H50/80

Abstract: The present disclosure relates to the early detection of the presence or occurrence of a condition in an object of investigation and/or the occurrence of an event in an object of investigation by means of machine learning methods. The subject matter of this disclosure consists of a computer-implemented method, a computer system, and a computer program for the early detection of such conditions and/or events.

公开(公告)号：US20240212811A1

公开(公告)日：2024-06-27

申请号：US18288963

申请日：2022-04-20

Applicant: Bayer Aktiengesellschaft

Inventor： Steffen VOGLER ,  Johannes HOEHNE ,  Matthias LENGA

IPC: G16H15/00 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80 ,  G16H10/60

CPC classification number: G16H15/00 ,  G06V10/774 ,  G06V10/776 ,  G06V10/803 ,  G16H10/60 ,  G06V2201/03

Abstract: A method for training a machine learning model that is able to establish links between data of different modalities by creating a joint representation. In particular, application of the method to medical data including electronic medical records and medical images and/or other medical data. The trained machine learning model can among others fulfil tasks such as autocompletion of incomplete data, detection of uncertain and/or spurious data, generation of probable data and other tasks.

公开(公告)号：US20240403625A1

公开(公告)日：2024-12-05

申请号：US18294532

申请日：2022-07-22

Applicant: Bayer Aktiengesellschaft

Inventor： Steffen VOGLER ,  Johannes HOEHNE ,  Matthias LENGA

IPC: G06N3/08 ,  G06V10/74 ,  G06V10/82 ,  G06V20/10

Abstract: The following disclosure relates to the field of data analysis, in particular medical data analysis, or more particularly relates to systems, apparatuses, and methods for processing in particular medical data stored in different modalities, so-called multi-modal data. In some embodiments, the disclosure relates to similarity retrieval for input data, in particular medical input data.

公开(公告)号：US20240289637A1

公开(公告)日：2024-08-29

申请号：US18573793

申请日：2022-06-17

Applicant: Bayer Aktiengesellschaft

Inventor： Matthias LENGA ,  Johannes HÖHNE ,  Steffen VOGLER

IPC: G06N3/098

CPC classification number: G06N3/098

Abstract: The present invention relates to the technical field of federated learning. Subject matter of the present invention is a method for (re-)training a federated learning system, a computer system for carrying out the method, and a non-transitory computer-readable storage medium comprising processor-executable instructions with which to perform an operation for (re-)training a federated learning system.

公开(公告)号：US20240005650A1

公开(公告)日：2024-01-04

申请号：US18038182

申请日：2021-11-12

Applicant: Bayer Aktiengesellschaft

Inventor： Jonas DIPPEL ,  Steffen VOGLER ,  Johannes HÖHNE

IPC: G06V10/82 ,  G06V10/774 ,  G06V10/75

CPC classification number: G06V10/82 ,  G06V10/7753 ,  G06V10/751

Abstract: Systems, methods, and computer programs disclosed herein relate to training of machine learning models on the basis of image training data with a limited number of labeled images.