research
∙
02/11/2023
Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes
Medical experts may use Artificial Intelligence (AI) systems with greate...
share
research
∙
07/06/2021
Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
Academic advances of AI models in high-precision domains, like healthcar...
research
∙
06/24/2021
Disease Progression Modeling Workbench 360
In this work we introduce Disease Progression Modeling workbench 360 (DP...
research
∙
05/16/2021
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
Accurate and explainable health event predictions are becoming crucial f...
research
∙
09/04/2020
Phenotypical Ontology Driven Framework for Multi-Task Learning
Despite the large number of patients in Electronic Health Records (EHRs)...
research
∙
07/24/2020
A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records
Many institutions within the healthcare ecosystem are making significant...
research
∙
03/23/2020
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes
Counterfactual prediction is a fundamental task in decision-making. G-co...
research
∙
11/15/2019
Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
In recent years, we have witnessed an increased interest in temporal mod...
research
∙
11/29/2017
A Novel Data-Driven Framework for Risk Characterization and Prediction from Electronic Medical Records: A Case Study of Renal Failure
Electronic medical records (EMR) contain longitudinal information about ...
research
∙
02/22/2017
Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources
Real-time monitoring and responses to emerging public health threats rel...
research
∙
06/01/2016
Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks
In retrospective assessments, internet news reports have been shown to c...
research
∙
03/31/2016
Hierarchical Quickest Change Detection via Surrogates
Change detection (CD) in time series data is a critical problem as it re...
research
∙
03/01/2016
