Function
Ref. Model
I/O Data
SubAIMs
JSON MData
Profiles
Ref. Software
Conformance
Performance
1 Functions
The Health Federated Learning (AIH‑HFL) AIM integrates into a new NN Model the knowledge acquired by trained NN Models participating in the Federated Learning process:
| Receives | Federated Learn Response | Response to Federated Learning Request containing the trained NN Model. |
| Produces | NN Model | NN Model submitted to MPAI Store. |
| Federated Learn Request | Request to Health Front End for a given NN Model. |
2 Reference Model
Figure 1 depicts the Reference Model of the Health Federated Learning (AIH‑HFL) AIM.
Figure 1 – The Health Federated Learning (AIH‑HFL) AIM Reference Model
3 I/O Data
Table 1 specifies the Input and Output Data of the Health Federated Learning (AIH‑HFL) AIM.
| Input | Description |
|---|---|
| Federated Learn Response | Response to Federated Learning Request containing the trained NN Model. |
| Output | Description |
| NN Model | NN Model submitted to MPAI Store. |
| Federated Learn Request | Request to Health Front End for a given NN Model. |
4 SubAIMs
No SubAIMs.
5 JSON Metadata
https://schemas.mpai.community/AIH1/V1.0/AIMs/HealthFederatedLearning.json
6 Profiles
No Profiles.
7 Reference Software
Under development.
8 Conformance Testing
Table 2 provides the Conformance Testing Method for the Health Federated Learning (AIH‑HFL) AIM.
If a schema contains references to other schemas, conformance of data for the primary schema implies that any data referencing a secondary schema shall also validate against the relevant schema, if present, and conform with the Qualifier, if present.
| Receives | Federated Learn Response | Shall validate against Federated Learn schema. |
| Produces | NN Model | Shall validate against ML Model Object schema. |
| Federated Learn Request | Shall validate against Federated Learn schema. |
9 Performance Assessment
Not part of this specification.
