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Found 6 papers, 4 papers with code
KindMed: Knowledge-Induced Medicine Prescribing Network for Medication Recommendation
Extensive adoption of electronic health records (EHRs) offers opportunities for its use in various clinical analyses.
A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions.
XADLiME: eXplainable Alzheimer's Disease Likelihood Map Estimation via Clinically-guided Prototype Learning
By considering this pseudo map as an enriched reference, we employ an estimating network to estimate the AD likelihood map over a 3D sMRI scan.
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Modeling non-Euclidean data is drawing extensive attention along with the unprecedented successes of deep neural networks in diverse fields.
Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series
In this work, we propose a novel variational-recurrent imputation network, which unifies an imputation and a prediction network by taking into account the correlated features, temporal dynamics, as well as the uncertainty.
Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction
However, once the missing values are imputed, most existing methods do not consider the fidelity or confidence of the imputed values in the modeling of downstream tasks.
