Results 31 to 40 of about 13,208 (247)

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

The Application of LightGBM in Microsoft Malware Detection

Journal of Physics: Conference Series, 2020
Abstract The development of new technologies has caused computers one of the most popular electronic products. However, there is always a number of people who intend to take advantages of others through attacking others’ computers. To avoid property damage as much as possible, a precise and efficient detection is essential.
Qiangjian Pan, Weiliang Tang, Siyue Yao
openaire   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Assessment of Stable Slopes Through BPSO-Driven Ensemble Models

Slovak Journal of Civil Engineering
This study explores a hybrid approach that combines BPSO with ensemble machine learning techniques to improve predictive accuracy in assessments of slope stability.
Anuragi Saurabh Kumar, Kishan D.
doaj   +1 more source

Landslide susceptibility evaluation considering the importance selection of influencing factors and soil moisture content

Shuiwen dizhi gongcheng dizhi
The current landslide susceptibility assessment system lacks unified and scientifically grounded standards for selecting factors that influence landslide development, leading to inconsistencies in evaluation results.
Zhongyu WANG, Sumin LI, Liwei YUAN, Weipeng LE   +3 more
doaj   +1 more source

Short term forecasting of base metals prices using a LightGBM and a LightGBM - ARIMA ensemble

Mineral Economics
Abstract Base metals are key materials for various industrial sectors such as electronics, construction, manufacturing, etc. Their selling price is important both for the profitability of the mining and metallurgical companies that produce and trade them, as well as for the countries whose economies rely on their exports or tax revenues as a ...
Konstantinos Oikonomou, Dimitris Damigos
openaire   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Assessment and Prediction of Typhoon-Related Direct Economic Loss in Fujian Province Based on LightGBM

Redai dili
Typhoons are among the most destructive natural disasters affecting China's coastal regions, often resulting in substantial economic loss and casualties.
Zhang Zhixia, Yang Jian, Chen Sixiao, Lin Sen   +3 more
doaj   +1 more source

Integrating machine learning, deep learning, and image analysis for seed species classification

Applications in Plant Sciences, EarlyView.
Abstract Premise The growing demand for wildflower seeds in ecological restoration requires reliable species identification, yet current market products often contain heterogeneous species. As seed identification is labor‐intensive and requires advanced botanical knowledge, we evaluated multiple segmentation and classification approaches to determine ...
Jonathan Ashworth, Eloise Barrett, Rebonto Haque, Ben Wildey, Anthony Hall, Felix Shaw, Jose J. De Vega   +6 more
wiley   +1 more source