techtimes

Leveraging Machine Learning Algorithms to Combat Fraud in Supply Chain Operations

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...
Forbes

Operational Excellence In MLOps

MLOps (machine learning operations) represents the integration of DevOps principles into machine learning systems, emerging as a critical discipline as organizations increasingly embed AI/ML into ...
Phys.org

Machine learning helps find advantageous combination of salts and organic solvents for easier anti-icing operations

An Osaka Metropolitan University research team has found a deicing mixture with high effectiveness and low environmental impact after using machine learning to analyze ice melting mechanisms of ...
Railway Age

Improving Rail Operations Using AI and Machine Learning: Detecting Trespasser Hotspots

TTC OPERATED BY ENSCO, RAILWAY AGE OCTOBER 2025 ISSUE: Trespassing along a rail corridor remains one of the most important and challenging issues that railroad operators face every day. Trespassing on ...
Nature

Integrating machine learning into business and management in the age of artificial intelligence

Machine Learning (ML), a facet of artificial intelligence (AI), utilizes computational methods to boost system performance by learning from experience, underpinned by mathematics, statistics, and ...
Hosted on MSN

The new standards of machine learning development

Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the largest possible models to see what capabilities might appear. Today, the ...
Forbes

Artificial Intelligence Or Machine Learning: What's Right For Your Business?

Artificial intelligence (AI) has transformed the business landscape and changed how we work. Its capability to automate tasks, analyze extensive datasets efficiently and provide concise business ...
ACHR News

AI-Based Control Algorithms: Sequence of Operations, Deep Learning, Machine Learning, and More

In the recent past, you probably attended a virtual lunch-and-learn presentation, read an article, or had a discussion with a controls sales representative in which the topic was a chilled water plant ...
ascopubs.org

Explainable Machine Learning Model to Preoperatively Predict Postoperative Complications in Inpatients With Cancer Undergoing Major Operations

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence–Based Prognosis for Patients With Advanced Solid Tumors Consecutive inpatients who underwent ...
Nature

An operational guide to translational clinical machine learning in academic medical centers

Few published data science tools are ever translated from academia to real-world clinical settings for which they were intended. One dimension of this problem is the software engineering task of ...
Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...