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Machine learning algorithms

A lightweight blockchain-inspired hybrid intrusion detection system with ensemble learning for tamper-proof auditing

Shailendra Mishra, Reem Alshenaifi, Ruba Ahmed Alfahidah

A bioinformatic single-cell and structure-informed framework identifies a baicalin–CA2–keratinocyte state axis in atopic dermatitis

Boyan Yang, Guilin Zhou, Jun Dai

Application of machine learning in predicting of MB2 canal in permanent maxillary first and second molars: A CBCT study

Ranjdar Mahmood Talabani

Prediction model for compressive strength of alkali-activated multi-source solid-waste grouting materials based on generative adversarial networks and machine learning

Qiang Yue, Guangming Yu, [ ... ], Guangwei Xiong

Forecasting alcohol lapse risk up to two weeks in advance using time-lagged machine learning models

Kendra Wyant, Gaylen E. Fronk, [ ... ], John J. Curtin

Lung cancer risk prediction using interpretable ensemble models on lifestyle and clinical data

Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Sensitivity of machine learning regression models to data structure and quality in crop yield prediction

Mahoukpégo Luc Zinzinhédo, Mèvognon Firmin Mitchozounnou, Kolawolé Valère Salako, Romain Glèlè Kakaï

Exploration of acetylation-related biomarkers in osteoarthritis through bioinformatics analysis

Shuchang Li, Jiefeng Yin, [ ... ], Jun Yao

Labeling matters: A multicenter machine learning study on visual field progression in Glaucoma

Hyobeen Kim, EunAh Kim, [ ... ], Jiwoong Lee

Comparative machine learning models for predicting the compressive strength of ultra-high-performance concrete

Nguyen Thi Thu Nga, Nguyen Anh Tuan, Nguyen Tuan Tu, Huyen Thi Dang

An efficient method for network traffic anomaly detection based on SHAP and deep learning

Zhaohui Fang, Ping Xuan, Hong Ding

Machine learning framework for predicting ESDD on high-voltage glass insulators with SHAP-based feature optimization

Ali Ahmed Salem, Waleed M. Hamanah, [ ... ], Samir Al-Gailani

ASWBoost: Classification algorithm for noisy and imbalanced data based on parametric exponential loss

Fei Meng, Mei Yan, [ ... ], Hao Li

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