We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...

Ultrafiltration membranes used in pharmaceutical manufacturing and other industrial processes have long relied on separating molecules by size. Now, Cornell researchers have created porous materials ...

Hidden Python libraries can make data analysis faster and easier for large datasets. Tools like Polars, Dask, and Sweetviz simplify data cleaning, modeling, and visualization. Learning new Python ...

Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .

For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Welcome to the Data Structures and Algorithms Repository! My aim for this project is to serve as a comprehensive collection of problems and solutions implemented in Python, aimed at mastering ...

Economists have developed different types of models describing the interaction of agents in markets. Early models in general equilibrium theory describe agents taking prices as given and do not ...

1 Department Health informatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia 2 Department of Community Health Nursing, School of Nursing ...