A nested-validation study in Victoria found that an interpretable XGBoost model could retrospectively concentrate crashes in ...

After nearly two years building an AI stock trading system, two AI models reached the same conclusion: don't turn it into a ...

For older adults with heart failure (HF), leaving the hospital alive does not always mean returning to an independent life. Loss of independence can ...

A model-development study using 471 specialist nurse samples achieved an AUC of 0.766 for distinguishing stated transfer ...

The polar vortex, a swirling mass of cold air encircling the North Pole, is sometimes disrupted by sudden stratospheric ...

Postquant Labs has launched its Quip Virtual Machine (QVM), a shared programming environment designed to run on leading ...

Artificial intelligence tools are being touted as a solution for so-called pajama time—the time doctors inevitably spend ...

Postquant Labs launched Quip Virtual Machine on the Aglais testnet, offering a shared programming and execution environment ...

For older adults with heart failure (HF), leaving the hospital alive does not always mean returning to an independent life.

Self-supervised learning creates training targets from the structure of unlabeled data, allowing models to learn ...

Scientists at UW-Madison have detailed a way to incorporate numerous forms of medical data into a set of machine learning models, in order to better predict the course of diseases such as cancer.

A new model accurately reproduces aspects of polar vortex behavior, extracting indicators of imminent vortex collapse and accompanying frigid weather in North America and Europe.