Search Results for author:
Found 5 papers, 3 papers with code
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis
For building a source model generally applicable to various tasks, we pre-train the model in a self-supervised learning manner for masked encoding vector prediction as a proxy task, using a large-scale normal, healthy brain magnetic resonance imaging (MRI) dataset.
Multi-view Integration Learning for Irregularly-sampled Clinical Time Series
In addition, we build an attention-based decoder as a missing value imputer that helps empower the representation learning of the inter-relations among multi-view observations for the prediction task, which operates at the training phase only.
Deep Recurrent Model for Individualized Prediction of Alzheimer's Disease Progression
While many of the previous works considered cross-sectional analysis, more recent studies have focused on the diagnosis and prognosis of AD with longitudinal or time series data in a way of disease progression modeling (DPM).
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.
