Securities.io

Crypto Security Needs Market-Aware Phishing Detection

In the modern age where most assets and valuable information are digitalized, phishing scams are an important way criminals steal money, much higher than “normal” physical robbery & extortion, with up ...
The Banker

Banks and regulators clash over ‘black box’ AI credit risk

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...
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 ...
Nature

XGBoost based machine learning prediction model for major adverse cardiovascular events after PCI in STEMI patients

ST-segment elevation myocardial infarction (STEMI) demands urgent reperfusion. Despite major strides in percutaneous coronary intervention (PCI), major adverse cardiovascular events (MACE) persist, ...
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 ...
LinkedIn

XGBoost: Machine Learning Powerhouse

In the world of data science, some tools are so practical that they seem to be everywhere. One of the most prominent is XGBoost, an algorithm that has become the gold standard for many predictive ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...
Nature

Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients

Following complete mesocolic excision (CME), heart failure (HF) emerges as a significant complication, exerting substantial impacts on both short-term and long-term patient prognoses. The primary ...