Patent ID: 11937932
Assignee: TUNGHAI UNIVERSITY
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 7:
8. The acute kidney injury predicting method of claim 5, wherein the model training step further comprises:
performing a federated learning step to drive the processor to upload a model parameter of the acute kidney injury prediction model to a cloud server for an auxiliary processing unit to download the model parameter from the cloud server, wherein the auxiliary processing unit trains the model parameter and a plurality of auxiliary detection data stored in an auxiliary memory according to the machine learning algorithm stored in the auxiliary memory to generate an auxiliary acute kidney injury prediction model and uploads an auxiliary model parameter of the auxiliary acute kidney injury prediction model to the cloud server, and the cloud server aggregates the model parameter and the auxiliary model parameter to create another acute kidney injury prediction model; and
performing a model verifying step to drive the processor to download the another acute kidney injury prediction model from the cloud server and input the data to be tested into the another acute kidney injury prediction model to generate another acute kidney injury characteristic risk probability, wherein the processor verifies whether the another acute kidney injury characteristic risk probability conforms to a real outcome;
wherein in response to determining that the another acute kidney injury characteristic risk probability does not conform to the real outcome, the processor repeatedly performs the federated learning step, until the another acute kidney injury characteristic risk probability conforms to the real outcome.