Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Recentive Analytics, Inc. v. Fox Corp., No. 23-2437 (Fed. Cir. 2025) – On April 18, 2025, the Federal Circuit upheld the district court’s dismissal of the case on the ground that the patents were ...

1 Beijing Forestry University, Beijing, China 2 Ecological Environment Monitoring Center, Sichuan Forestry and Grassland Survey and Planning Institute, CHENGDU, China The final, formatted version of ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...

Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.

(2026) AI Assisted Material Selection Framework for Corrosion Resistant Steels in Onshore Oil and Gas Pipelines. Open Journal ...

Modern forex trading heavily depends on advanced analytics, machine learning, and real-time data processing. Big data platforms are boosting forecasting ...

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...

Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...