Search Results for author:
Found 8 papers, 0 papers with code
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.
Surrogate Ensemble Forecasting for Dynamic Climate Impact Models
Seasonal ensembles forecasts of temperature and precipitation with a 6-month horizon are propagated through the model, predicting the distribution of transmission time series.
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.
Overcoming Digital Gravity when using AI in Public Health Decisions
In popular usage, Data Gravity refers to the ability of a body of data to attract applications, services and other data.
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.
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.
Novel Exploration Techniques (NETs) for Malaria Policy Interventions
The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity.
