flwr new @javier/iron-deficiency

Federated Iron-Deficiency Classification

This Flower app trains a PyTorch binary classifier to identify iron deficiency from routine complete blood count measurements and age. Iron deficiency is defined as ferritin below 15 ng/mL.

The federation has four clients, each representing a different NHANES survey cycle: 2005–2006, 2015–2016, 2017–2018, and 2021–2023. Each client trains on its own locally standardized data.

Deployment federation

The app is designed for a deployment federation with four SuperNodes. Each SuperNode must be assigned exactly one of the four survey cycles through its node configuration. For example:

flower-supernode \
  --insecure \
  --superlink <superlink-host>:9092 \
  --node-config "CYCLES='2005-2006'" \
  --allow-runtime-dependency-installation # optional

Launch the other three SuperNodes in the same way, setting CYCLES to 2015-2016, 2017-2018, and 2021-2023, respectively. The CYCLES argument is required because it determines which NHANES partition the client loads.

The dataset is built from the NHANES demographics, complete blood count, and ferritin components. It includes women aged 18–49 with complete measurements, using 13 blood-count variables plus age as model features. Missing files are downloaded from NHANES and cached when each client first loads its data.