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US 2025/0156757 A1Published application
Client-based re-training and evaluation of artificial-intelligence model
AssigneeSiemens Healthineers AG
InventorsAnna Jerebko, Varghese Kollerathu
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Abstract
The present disclosure relates deployment of an artificial intelligence model from a central server. The disclosure further relates to client-based re-training and validation of an artificial intelligence model at multiple clients.
Claims20
A computer-implemented method, comprising:
- deploying an artificial intelligence model in a first training state to multiple clients;
- at each of the multiple clients, acquiring a respective training dataset;
- at each of the multiple clients, re-training the artificial intelligence model to obtain the artificial intelligence model in a second training state;
- associating the multiple clients with multiple groups;
- for each of the multiple groups, aggregating weights of the artificial intelligence model in the second training state associated with clients within the respective group, to obtain the artificial intelligence model in a third training state;
- and
- evaluating the artificial intelligence model in each of the third training states.
4 more elements
A computer-implemented method for use in a client, comprising:
- obtaining, from a central authority, an artificial intelligence model in a first training state;
- performing inference based on the artificial intelligence model in the first training state;
- acquiring a training dataset based on said performing of the inference;
- re-training the artificial intelligence model based on the training dataset, to obtain the artificial intelligence model in a second training state;
- providing the artificial intelligence model in the second training state to at least one of the central authority and one or more further clients;
- establishing the artificial intelligence model in multiple third training states based on information obtained from at least one of the central authority or the one or more further clients;
- and
- evaluating the artificial intelligence model in each of the multiple third training states based on benchmarking against performance of the artificial intelligence model in the third training state and based on the training dataset.
5 more elements
A device, comprising:
- non-transitory computer-readable medium for storing program code;
- and
- one or more processor units in communication with the non-transitory computer-readable medium, the one or more processor units being operative with the program code to perform operations including
- obtaining, from a central authority, an artificial intelligence model in a first training state,
- performing inference based on the artificial intelligence model in the first training state,
- acquiring a training dataset based on said performing of the inference,
- re-training the artificial intelligence model based on the training dataset, to obtain the artificial intelligence model in a second training state,
- providing the artificial intelligence model in the second training state to at least one of the central authority and one or more further clients,
- establishing the artificial intelligence model in multiple third training states based on information obtained from at least one of the central authority or the one or more further clients, and
- evaluating the artificial intelligence model in each of the multiple third training states based on benchmarking against performance of the artificial intelligence model in the third training state and based on the training dataset.
7 more elements
Dependencies are inferred from the claim text.