Harvard Business Review

What the Best AI Users Do Differently—and How to Level Up All of Your Employees

Leaders often struggle to assess whether their employees are using AI successfully. Often, they default to measuring what’s easily observable: how much they’re using AI tools. To get a clearer picture ...
IEEE

Machine Learning-based Malware Detection on Android Operating System using AdaBoost Algorithm and ReliefF Feature Selection Method

Abstract: Technological advancements occur rapidly from year to year. Currently, we experience the benefits of this rapid technological development, including the widespread use of smartphones in our ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
Phys.org

Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...
Finbold | Finance in Bold

Machine learning algorithm predicts Bitcoin price on January 31, 2026

After apparently promising a climb back to $100,000 for about a week, Bitcoin (BTC) suddenly reversed late on Sunday, January 18, and ended up trading at $93,013 by press time on Monday. BTC price ...
Finbold | Finance in Bold

Machine learning algorithm predicts XRP price on January 31, 2026

XRP has lost some steam over the past twenty-four hours as the Senate delayed a key crypto market structure bill on January 15. At the same time, daily trading volume slipped 30% as the broader market ...
Frontiers

A machine learning model for assessing fetal health during pregnancy

There is a global imperative to end stillbirths, particularly in low middle income countries (LMICs), which suffer from disproportionate incidence. Sudden changes in fetal movement (FM) patterns often ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

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

Machine Learning Algorithm Predicts Gout Flares Using RNA

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
ahajournals.org

Abstract 4340723: Comparative Study of Coronary Artery Disease (CAD) Prediction: Conventional QRISK3 vs. Enhanced Machine Learning Models Combined with Particle Swarm ...

Background: Coronary Artery Disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known ...
IEEE

Mapping Soil Organic Matter in Cultivated Land Using Landsat 8 Image and GA-AdaBoost Algorithm

Abstract: Soil organic matter (SOM) is essential for maintaining soil structure, nutrient supply, and water regulation in cultivated land, significantly impacting agricultural productivity and the ...