Requirements Federated Learning and mUlti-party computation Techniques for prostatE cancer
0.1.0 - ci-build
Funded by the European Union

Requirements Federated Learning and mUlti-party computation Techniques for prostatE cancer, published by HL7 Europe. This guide is not an authorized publication; it is the continuous build for version 0.1.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/hl7-eu/flute-requirements/ and changes regularly. See the Directory of published versions

Requirements: NF-IMSD-4

Official URL: https://flute.com/Requirements/NF-IMSD-4 Version: 0.1.0
Draft as of 2023-10-25 Computable Name: NF_IMSD_4

Copyright/Legal: HL7 Europe

ID: NF-IMSD-4

Publisher: HL7 Europe

Contact Name Contact Points
HL7 Europe

Description:

Synthetic data used in combination with real data (data augmentation) improves the prediction performance of the algorithms trained using only real data.

Purpose:

Set of data and algorithmic requirements of both the developers and the users.

Copyright Label: Federated Learning and mUlti-party computation Techniques for prostatE cancer


Statements:

ID: NF-IMSD-4

Label: Synthetic data used in combination with real data (data augmentation) SHOULD improves the prediction performance of the algorithms trained using only real data.

Sources:

  • HL7 Europe
Conformance Requirement
SHOULD

improves the prediction performance of the algorithms trained using only real data