A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

A machine learning model predicts progression independent of relapse activity (PIRA) in early multiple sclerosis. Key predictors for PIRA include age at symptom onset, early disability scores, and ...

This repository contains the official implementation and data for the paper "Can We Predict Before Executing Machine Learning Agents?". Traditional machine learning agents rely on an iterative ...

Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods have shown ...

Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

Abstract: Traffic congestion prediction plays a crucial role in enabling next-generation Intelligent Transportation Systems (ITS) for smart cities. However, existing approaches often face trade-offs ...

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study ...