Polymer-chemistry dataset created for training AI models

Polymers are fundamental to our daily lives, serving as the core components for a wide array of goods, including clothing, packaging, transportation infrastructure, construction materials, and ...
Frontiers

Machine Learning and AI-Driven Biomechanics in Orthopedic Surgery

Rapid advances in artificial intelligence, machine learning, and data-driven computational modeling have opened unprecedented opportunities to transform ...
Devdiscourse

Next-gen AI biosensors promise faster, smarter pandemic surveillance

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
Devdiscourse

AI failures start with bad data

The study An actionable framework for AI-ready data, published in AI Magazine, presents a practical roadmap for strengthening the foundations of artificial intelligence. It details how organizations ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Scientific Research Publishing

An Empirical Study Based on Big Data Analysis to Analyze Social Media Group Sentiment and Its Impact on Consumer Psychology ()

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...
Kennesaw State University

Supercomputing research at KSU speeds up the path to scientific discovery

From space exploration to artificial intelligence, modern scientific breakthroughs depend on moving large amounts of data quickly. At Kennesaw State University, Associate Professor of Information ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

Impact of Data Preprocessing on Machine Learning Classification Metrics

Abstract: Data preparation is essential for boosting machine learning model's performance by increasing data quality and lowering noise. This study evaluates the impact of preprocessing on key ...