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US 11,538,152 B2Granted
Method for providing an aggregate algorithm for processing medical data and method for processing medical data
AssigneeSiemens Healthcare GmbH
InventorsChristian Schmidt, Max Schoebinger, Michael Wels
Life of this patent
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Abstract
A method is for providing an aggregate algorithm for processing medical data. In an embodiment, a multitude of local algorithms are trained by machine learning. The training of each respective local algorithm is performed on a respective local system using respective local training data. A respective algorithm dataset concerning the respective local algorithm is transferred to an aggregating system that generates the aggregate algorithm based on the algorithm datasets.
Claims21
A method for providing an aggregate algorithm for processing medical data, the method comprising:
- training a plurality of local algorithms by machine learning by training each respective local algorithm, of the plurality of local algorithms, on a respective local system using respective local training data;
- transferring a plurality of algorithm datasets corresponding to the plurality of local algorithms, respectively, to an aggregating system, each algorithm dataset of the plurality of algorithm datasets including at least one of a complete algorithm of the respective local algorithm or parameters for parameterizing a basic algorithm to reconstruct the respective local algorithm;
- and
- generating the aggregate algorithm by combining outputs of the plurality of local algorithms by at least one of
- a weighted or non-weighted averaging, or
- majority voting.
3 more elements
A system comprising:
- at least one processor configured to cause the system to
- train a plurality of local algorithms by machine learning by training each respective local algorithm, of the plurality of local algorithms, on a respective local system using respective local training data;
- transfer a plurality of algorithm datasets corresponding to the plurality of local algorithms, respectively, to an aggregating system, each algorithm dataset of the plurality of algorithm datasets including at least one of a complete algorithm of the respective local algorithm or parameters for parameterizing a basic algorithm to reconstruct the respective local algorithm;
- and
- generate the aggregate algorithm by combining outputs of the plurality of local algorithms by at least one of
- a weighted or non-weighted averaging, or
- majority voting.
4 more elements
Dependencies are inferred from the claim text.