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Classification on AI-READI Full (train)

71.8Accuracy

NN

Updated 4d ago

Evaluation Results

Method	Links
NN 2026.01		71.8	68	68	68	78

SOTA Paper

NN

Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation

Dataset

AI-READI

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Related Benchmarks

Counterfactual Generation on AI-READI Class 0 Counterfactual Generation on AI-READI (Class 1)Classification on AI-READI Scenario A — Positive-Class Undersampling (train)Classification on AI-READI Scenario B — Negative-Class Undersampling (train)Classification on AI-READI Scenario C — Dual-Class Undersampling (train)

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