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  1. 941
  2. 942

    Multiple machine learning algorithms identify 13 types of cell death-critical genes in large and multiple non-alcoholic steatohepatitis cohorts by Renao Jiang, Longfei Dai, Xinjian Xu, Zhen Zhang

    Published 2025-05-01
    “…Consensus clustering analysis was then used to stratify patients with NASH into distinct phenotypic subgroups based on expression levels of these genes. Results A NASH prediction model, developed using the random forest (RF) algorithm, demonstrated high diagnostic accuracy across multiple cohorts. …”
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    Article
  3. 943
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    Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

    Published 2025-01-01
    “…Additionally, we developed a Multi-Objective Genetic Algorithm (MOGA)-enhanced RNN model to optimize hyperparameters and achieve accurate traffic speed predictions. …”
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  5. 945

    iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction by Bicheng Ye, Jun Fan, Lei Xue, Yu Zhuang, Peng Luo, Aimin Jiang, Jiaheng Xie, Qifan Li, Xiaoqing Liang, Jiaxiong Tan, Songyun Zhao, Wenhang Zhou, Chuanli Ren, Haoran Lin, Pengpeng Zhang

    Published 2025-04-01
    “…Abstract To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi‐omics data integration. …”
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    Article
  6. 946
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    Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

    Published 2025-01-01
    “…The ARDL-FDIAR technique uses Z-score normalization to scale the input data. The attribute reduction process gets invoked using the modified Lemrus optimization algorithm (MLOA) to choose optimal feature sets. …”
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    Article
  8. 948

    A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

    Published 2022-12-01
    “…Based on the data of a distribution network expansion project of a power supply bureau, the simulation results show that the classification accuracy of the algorithm used in this paper is better than other algorithms. …”
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  9. 949
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    A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement by Minjuan WANG, Zhengpeng JI, Chao LV

    Published 2016-05-01
    “…An algorithm model conformed to the user behavior,based on the massive IPTV user characteristic data which extract rules and classify IPTV users was proposed.First,IPTV user group description dimension in accordance with the user on demand was put forward.Namely,the user group could be described by basic property and trend of user behavior could be described by users' demand behavior.Then the concept of prediction measurement was put forward,the stability of user group was described,and an algorithm which extracted demand behavior probability on stable user group was proposed.At last,the algorithm model was verified and analyzed by massive IPTV operation data.…”
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    Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

    Published 2025-01-01
    “…This study leverages the UCI heart disease dataset to assess the effectiveness of various Machine Learning models in predicting heart diseases. This paper proposed an advanced prediction method that combines feature selection using a hybrid of Genetic Algorithm (GA) and Cuckoo Search Optimization (CSO) with a majority voting ensemble of Convolutional Neural Network and Random Forest. …”
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    Preliminary Evaluation of an Advanced Ventilation-Control Algorithm to Optimise Microclimate in a Commercial Broiler House by Kehinde Favour Daniel, Lak-yeong Choi, Se-yeon Lee, Chae-rin Lee, Ji-yeon Park, Jinseon Park, Se-woon Hong

    Published 2024-11-01
    “…This study aims to improve the microclimate conditions in a mechanically ventilated broiler house by proposing and evaluating a ventilation-control algorithm based on heat-energy balance analysis. The new algorithm is designed to optimise the ventilation-rate requirement and thereby improve control of the indoor temperature. …”
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  17. 957

    Model Data Mining sebagai Prediksi Penyakit Hipertensi Kehamilan dengan Teknik Decision Tree by Ari Muzakir, Rika Anisa Wulandari

    Published 2016-06-01
    Subjects: “…Data mining, Decision tree, C4.5 algorithms, Prediction, Pregnancy…”
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    Article
  18. 958
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    Postpartum Haemorrhage Risk Prediction Model Developed by Machine Learning Algorithms: A Single-Centre Retrospective Analysis of Clinical Data by Wenhuan Wang, Chanchan Liao, Hongping Zhang, Yanjun Hu

    Published 2024-03-01
    “…This study used machine learning algorithms and new feature selection methods to build an efficient PPH risk prediction model and provided new ideas and reference methods for PPH risk management. …”
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    Article
  20. 960

    Integrative machine learning approach for forecasting lung cancer chemosensitivity: From algorithm to cell line validation by Jinghong Chen, Yonglin Yi, Chunqian Yang, Haoxuan Ying, Jian Zhang, Anqi Lin, Ting Wei, Peng Luo

    Published 2025-01-01
    “…Methods: This study developed a model to predict chemotherapy response in lung cancer patients by integrating multi-omics and clinical data from the Genomics of Drug Sensitivity in Cancer database, employing 45 machine learning algorithms. …”
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    Article