Results 121 to 130 of about 38,464 (255)

Multi-Objective artificial bee colony optimized hybrid deep belief network and XGBoost algorithm for heart disease prediction. [PDF]

Front Digit Health, 2023
Kalita K, Ganesh N, Jayalakshmi S, Chohan JS, Mallik S, Qin H.   +5 more
europepmc   +1 more source

Particle Swarm Optimization as a Noise‐Tolerant Strategy for High‐Entropy Alloy Research

Advanced Intelligent Discovery, EarlyView.
A customized particle swarm optimization algorithm is benchmarked against batch Bayesian optimization across four high‐entropy alloy oxygen‐reduction landscapes. While both methods locate the global optimum comparably under noise‐free conditions, Bayesian optimization’s surrogate model tends to overfit noisy data.
Ahmad Tirmidzi, Matthias Arenz, Vladislav A. Mints   +2 more
wiley   +1 more source

A study on predicting the length of hospital stay for Chinese patients with ischemic stroke based on the XGBoost algorithm. [PDF]

BMC Med Inform Decis Mak, 2023
Chen R, Zhang S, Li J, Guo D, Zhang W, Wang X, Tian D, Qu Z, Wang X.   +8 more
europepmc   +1 more source

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features. [PDF]

J Clin Med, 2023
Lin X, Chen L, Zhang D, Luo S, Sheng Y, Liu X, Liu Q, Li J, Shi B, Peng G, Zhong X, Huang Y, Li D, Qin G, Yin Z, Xu J, Meng C, Liu Y.   +17 more
europepmc   +1 more source

Deep Learning Classification of Pancreatic Cancer Cells Over a Progression of Epithelial to Mesenchymal States by Deformability Cytometry Under Microfluidic Viscoelastic Flows

Advanced Intelligent Systems, EarlyView.
Cancer cells progressively spread over intermediate epithelial‐to‐mesenchymal transition states that cause nuclear enlargement and circular redistribution of filamentous vimentin are classified by deformability cytometry coupled to a multi‐region deep learning model with convolutional feature extraction and attention‐based regional aggregation.
Javad Jarmoshti, Hanyuan Gao, Negin Zeinali, Abdullah‐Bin Siddique, Sara J. Adair, Todd W. Bauer, Matthew J. Lazzara, Xiaoxuan Yang, Nathan S. Swami   +8 more
wiley   +1 more source

Ultra-short-term wind power prediction method combining financial technology feature engineering and XGBoost algorithm. [PDF]

Heliyon, 2023
Guan S, Wang Y, Liu L, Gao J, Xu Z, Kan S.   +5 more
europepmc   +1 more source

MetaPaCS: A Novel Meta‐Learning Framework for Pancreatic Cancer Subtype Identification

Advanced Intelligent Systems, EarlyView.
We have developed MetaPaCS, an ensemble meta‐learning framework for reliable prediction of pancreatic cancer subtypes with high accuracy. MetaPaCS is capable of capturing subtype‐specific distinct gene expression patterns and drug‐disease associations for pancreatic cancer.
Nick B. Peterson, Mengtao Sun, Xinchao Wu, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Impact of COVID-19 on mental health in China: analysis based on sentiment knowledge enhanced pre-training and XGBoost algorithm. [PDF]

Front Public Health, 2023
Huang R, Wang X.
europepmc   +1 more source

Advancing Environmental Sustainability: The Role of Artificial Intelligence in Monitoring, Predicting, and Controlling Sulfur Dioxide Emissions

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Air pollution from sulfur dioxide (SO2) emissions poses significant threats to environmental sustainability, public health, and climate change efforts. Despite advances in monitoring and regulatory frameworks, traditional methods often fall short in accuracy, scalability, and efficiency.
Turkan Kopac
wiley   +1 more source