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Found 8 papers, 0 papers with code
Domain-agnostic and Multi-level Evaluation of Generative Models
To this end, we propose a framework for Multi-level Performance Evaluation of Generative mOdels (MPEGO), which could be employed across different domains.
A Collaborative Approach to the Analysis of the COVID-19 Response in Africa
The COVID-19 crisis has emphasized the need for scientific methods such as machine learning to speed up the discovery of solutions to the pandemic.
Model-free feature selection to facilitate automatic discovery of divergent subgroups in tabular data
Existing feature selection techniques for tabular data often involve fitting a particular model in order to select important features.
Sparsity-based Feature Selection for Anomalous Subgroup Discovery
However, there is a common lack of a principled and scalable feature selection method for efficient discovery.
Post-discovery Analysis of Anomalous Subsets
Analyzing the behaviour of a population in response to disease and interventions is critical to unearth variability in healthcare as well as understand sub-populations that require specialized attention, but also to assist in designing future interventions.
Automated Supervised Feature Selection for Differentiated Patterns of Care
The pipeline included three types of feature selection techniques; Filters, Wrappers and Embedded methods to select the top K features.
Disease Progression Modeling Workbench 360
In this work we introduce Disease Progression Modeling workbench 360 (DPM360) opensource clinical informatics framework for collaborative research and delivery of healthcare AI.
WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6, 000 NPIs implemented worldwide since the start of the pandemic.
