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 ...

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.

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 ...

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...