Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...

A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of a next-generation biocompatible titanium alloy, potentially improving the ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Calsoft introduced an AI-powered approach to Test Impact Analysis that eliminates unnecessary test executions in CI/CD ...