EurekAlert!

Image-based machine learning framework sharpens battery health estimation across varying conditions

Researchers have developed an integrated framework for estimating battery state of health, or SOH, by combining incremental ...
Open Heart

Periprocedural evaluation of patients with BAV stenosis undergoing TAVR: a machine learning-based study

Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
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

Zhang, Y., & Zheng, Y. (2023). Estimating Response Propensities in Nonprobability Surveys Using Machine Learning. Journal of Survey Statistics and Methodology, 11, 123-145.

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 ...
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 ...
Frontiers

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...
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 ...
Frontiers

Bacteriocin prediction through cross-validation-based and hypergraph-based feature evaluation approaches

Bacteriocins offer a promising solution to antibiotic resistance, possessing the ability to target a wide range of bacteria with precision. Thus, there is an urgent need for a computational model to ...
GitHub

Classification task using GLM, XGBoost and AutoML

As an assignment under the module of Applied Machine Learning, our task was to create 3 classification models and compete on a private Kaggle competition. The data provided had 97 masked variables. I ...