Fair Gated Algorithm for Targeted Equity
Analyse and Visualise Expert Network Specialisation
Analyse and Visualise GNN Results
Export predictions for IBM Fairness 360
Create a Sankey Plot (robust; aggregates to one row per subject)
Prepare Data for GNN Training
Train and Evaluate the Gated Neural Network (robust splits + safe ROC)
Tools for training and analysing fairness-aware gated neural networks for subgroup-aware prediction and interpretation in clinical datasets. Methods draw on prior work in mixture-of-experts neural networks by Jordan and Jacobs (1994) <doi:10.1007/978-1-4471-2097-1_113>, fairness-aware learning by Hardt, Price, and Srebro (2016) <doi:10.48550/arXiv.1610.02413>, and personalised treatment prediction for depression by Iniesta, Stahl, and McGuffin (2016) <doi:10.1016/j.jpsychires.2016.03.016>.