Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

SMEs are widely recognized as the backbone of Europe’s economy, yet many face persistent challenges in accessing equity ...

Biochar, a carbon-rich material made from organic waste, is gaining attention for its ability to improve soils, clean water, and capture carbon. A new review in Biochar X highlights how machine ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional methods of contract analytics are time-consuming and often inexact, thus ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

The study, titled "Machine Learning Technique for Carbon Sequestration Estimation of Mango Orchards Area Using Sentinel-2 Data," is led by Prof. Sittichai Choosumrong from the Department of Natural ...

The new AI model uses epigenetic data to predict long-term CHO stability and relies on machine learning techniques, such as random forest.

Machine Learning Models: Using algorithms like neural networks and random forests, these models train prediction models from large samples of match data, gradually improving accuracy. This shift marks ...

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.