In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual reviews of satellite images taking multiple months, land-use change can ...

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic ...

Abstract: Heavy rainfall prediction is crucial for various applications such as flood forecasting, water resource management, and agriculture. In this study, we propose a multi linear regression ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...

Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...