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 ...

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 ...

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 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.