EurekAlert!

Hybrid modeling strategy based on deep learning surrogate models enables accurate multi-objective optimization of iso-octanol oxidation

Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven ...
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 ...
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 ...
Morning Overview on MSN

AI tool aims to flag health care needs of childhood cancer survivors

Researchers are testing whether natural language processing can detect hidden psychological distress in childhood cancer ...
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 ...
Scientific Research Publishing

Chen, T., & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ...

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 ...
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 ...
C&EN

Enhancing Engine Performance and Sustainability: Gold Nanoparticles and Machine Learning for Biodiesel Optimization in Compression Ignition Systems

Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...