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09/14/2023
Supporting Management of Gestational Diabetes with Comprehensive Self-Tracking: Mixed-Method Study of Wearable Sensors
Gestational diabetes (GDM) poses a growing health risk to both pregnant ...
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09/12/2023
Content Reduction, Surprisal and Information Density Estimation for Long Documents
Many computational linguistic methods have been proposed to study the in...
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06/18/2023
Identifiable causal inference with noisy treatment and no side information
In some causal inference scenarios, the treatment (i.e. cause) variable ...
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06/16/2023
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions
Deciding on an appropriate intervention requires a causal model of a tre...
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03/17/2023
ASymReg: Robust symmetric image registration using anti-symmetric formulation and deformation inversion layers
Deep learning based deformable medical image registration methods have e...
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01/25/2023
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection
Adverse drug events (ADEs) are an important aspect of drug safety. Vario...
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11/14/2022
Modeling MRSA decolonization: Interactions between body sites and the impact of site-specific clearance
MRSA colonization is a critical public health concern. Decolonization pr...
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09/09/2022
Joint Non-parametric Point Process model for Treatments and Outcomes: Counterfactual Time-series Prediction Under Policy Interventions
Policy makers need to predict the progression of an outcome before adopt...
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08/26/2022
Deformation equivariant cross-modality image synthesis with paired non-aligned training data
Cross-modality image synthesis is an active research topic with multiple...
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07/04/2022
Look beyond labels: Incorporating functional summary information in Bayesian neural networks
Bayesian deep learning offers a principled approach to train neural netw...
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01/31/2022
Deconfounded Representation Similarity for Comparison of Neural Networks
Similarity metrics such as representational similarity analysis (RSA) an...
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01/08/2022
A Unified Review of Deep Learning for Automated Medical Coding
Automated medical coding, an essential task for healthcare operation and...
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09/07/2021
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning
Multitask deep learning has been applied to patient outcome prediction f...
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09/06/2021
Multi-task Balanced and Recalibrated Network for Medical Code Prediction
Human coders assign standardized medical codes to clinical documents gen...
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08/31/2021
Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records
We leverage deep sequential models to tackle the problem of predicting h...
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05/27/2021
Deep Learning for Depression Recognition with Audiovisual Cues: A Review
With the acceleration of the pace of work and life, people have to face ...
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04/02/2021
Multitask Recalibrated Aggregation Network for Medical Code Prediction
Medical coding translates professionally written medical reports into st...
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03/11/2021
Does the Magic of BERT Apply to Medical Code Assignment? A Quantitative Study
Unsupervised pretraining is an integral part of many natural language pr...
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02/12/2021
A Critical Look At The Identifiability of Causal Effects with Deep Latent Variable Models
Using deep latent variable models in causal inference has attracted cons...
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10/14/2020
Medical Code Assignment with Gated Convolution and Note-Code Interaction
Medical code assignment from clinical text is a fundamental task in clin...
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09/30/2020
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text
Medical code assignment, which predicts medical codes from clinical text...
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02/24/2020
Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks
Encoding domain knowledge into the prior over the high-dimensional weigh...
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02/02/2020
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Human knowledge provides a formal understanding of the world. Knowledge ...
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10/14/2019
Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation
Surrogate models such as Gaussian processes (GP) have been proposed to a...
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10/14/2019
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
Surrogate models such as Gaussian processes (GP) have been proposed to a...
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06/10/2019
Errors-in-variables Modeling of Personalized Treatment-Response Trajectories
Estimating the effect of a treatment on a given outcome, conditioned on ...
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05/03/2019
Parallel Gaussian process surrogate method to accelerate likelihood-free inference
We consider Bayesian inference when only a limited number of noisy log-l...
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01/24/2019
Recovering Pairwise Interactions Using Neural Networks
Recovering pairwise interactions, i.e. pairs of input features whose joi...
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11/27/2018
A Bayesian model of acquisition and clearance of bacterial colonization
Bacterial populations that colonize a host play important roles in host ...
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05/09/2017
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Predicting the efficacy of a drug for a given individual, using high-dim...
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04/03/2017
Efficient acquisition rules for model-based approximate Bayesian computation
Approximate Bayesian computation (ABC) is a method for Bayesian inferenc...
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12/07/2016
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
Providing accurate predictions is challenging for machine learning algor...
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10/20/2016
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Approximate Bayesian computation (ABC) can be used for model fitting whe...
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10/27/2014