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REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling

NeurIPS 2023 · Label-efficient and robust learning › Recognition and long-tail · approach: Recommendation representation learning · 12 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add all trend information (dosage and lab slope/variance) (ablation)REFINE · MIMIC-IVPR-AUC: 0.682 -> 0.708Helped
add all trend information (ablation)REFINE · PRIVATEPR-AUC: 0.703 -> 0.729Helped
add medication dosage trend (ablation)REFINE · MIMIC-IVPR-AUC: 0.701 -> 0.708Helped
add lab test trend (ablation)REFINE · MIMIC-IVPR-AUC: 0.695 -> 0.708Helped
add drug interaction severity weighting (ablation)REFINE · MIMIC-IVPR-AUC: 0.694 -> 0.708Helped
add drug interaction severity weighting (ablation)REFINE · PRIVATEwDDI: 0.115 -> 0.111Helped
add drug interaction severity weighting (ablation)REFINE · PRIVATEF1: 0.639 -> 0.656Helped
REFINE instead of MoleRecmedication recommendation · MIMIC-IVF1: 0.579 -> 0.635Helped

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