Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Machine Learning Is Enabling A New Era For Precision Medicine And Pharmacogenomics

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Wastewater management reverses widespread freshwater deoxygenation in China

Freshwater ecosystems worldwide have been suffering from declining oxygen levels—a trend known as deoxygenation—that ...
Frontiers

Non-invasive prediction of detrusor underactivity in benign prostatic hyperplasia: an interpretable machine learning framework to optimize surgical selection

This retrospective cohort study enrolled 538 urodynamically evaluated BPH patients. A rigorous multidimensional feature selection pipeline (LASSO, Boruta, and Recursive Feature Elimination) distilled ...
IEEE

Real-time Analysis of DDoS Attack Detection and Mitigation Measures Using XGBoost Machine Learning Algorithm

Abstract: Distributed Denial of Service (DDoS) attacks pose an ongoing threat to networked systems, often disrupting services and compromising data integrity. This study presents a real-time approach ...
Scientific Research Publishing

Dinov, I. D. (2023). Model Performance Assessment, Validation, and Improvement. In editor (Ed.), The Springer Series in Applied Machine Learning (Vol. 2853, pp. 477-531 ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...
EurekAlert!

Intelligent XGBoost framework enhances asphalt pavement skid resistance assessment

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...
IEEE

Explainable Machine Learning for Sleep Health Analysis Using XGBoost and SHAP Interpretability

With the integration of machine learning techniques into the medical field, there has been a sea change in the last couple of years, and a new era of innovation seems to usher in precision healthcare ...
Scientific Research Publishing

Liang, W., Luo, S., Zhao, G. and Wu, H. (2020) Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms. Mathematics, 8, Article No. 765.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...