Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
Morning Overview on MSN
Machine learning is turbocharging cheap lithium-ion battery design
Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...
The Southern Maryland Chronicle on MSN
How are QA teams using machine learning to predict test failures in real time?
QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.
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 ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Data is the new fuel. The potential for machine learning and deep learning practitioners to make a breakthrough and drive positive outcomes is unprecedented. But how to take advantage of the myriad of ...
The Punch on MSN
How Betting Platforms Use Machine Learning for Fraud Detection
Fraud remains one of the biggest challenges for betting platforms. This article explains how machine learning helps spot ...
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