David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...

Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

An artificial intelligence (AI) machine-learning model has been developed that can predict the risk of early death in trauma ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

The human brain is known to naturally change with age, shrinking in size and volume after people reach their 30s or 40s. In ...

Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Investigators assessed whether machine learning models provide accurate, individualized risk predictions for major 30-day postoperative complications following glossectomy.

Large-scale recommendation systems are becoming harder to improve because they no longer operate as isolated models. Modern ...

The initiative aims to address the growing threat of floods, which claim lives and displace lakhs of people due to flash ...

The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.