Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
Most companies today are building their AI strategy around structured data because unstructured data is operationally hard.
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Overparameterized neural networks: Feature learning precedes overfitting, research finds
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.
You will be redirected to our submission process. Integrating data and models is essential for advancing our understanding and management of water resources in an era of rapid environmental change.
Using data analytics – and, ironically, some artificial intelligence – a team at Cornell University has mapped the environmental impact of AI by state. They published their results in the journal ...
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