New research shows supervised machine learning models combining Helicobacter pylori genomic data with patient demographics can accurately predict gastric cancer risk.

Artificial intelligence has moved from crunching physics data in the background to actively proposing new theories and ...

Intel is looking for a Data Scientist who specializes in Demand and Supply Planning to develop advanced analytics and machine learning systems that will optimiz ...

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...

Investments in automation and additional tools for data analytics keep coming to packaging lines as plants become more connected. Machine learning and digital twin technology are increasing throughput ...

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 ...

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

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity ...

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 ...

Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...