A Risk-Optimized Framework for Data-Driven IPO Underperformance Prediction in Complex Financial Systems by Mazin Alahmadi

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BiLSTM-Based Parallel CNN Models With Attention and Ensemble Mechanism for Twitter Sentiment Analysis by Anas W. Abulfaraj

“…Our methodology incorporates four classifiers to produce text class predictions. Among them, five algorithms are selected for evaluation: Ridge Classifier (RC), Linear Discriminant Analysis (LDA), Extra Trees (ET), and Light Gradient Boosting Machine (LightGBM). …”
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Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks by Yusuf Secgin, Seren Kaya, Oğuzhan Harmandaoğlu, Oğuzhan Öztürk, Deniz Senol, Ömer Önbaş, Nihat Yılmaz

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An extensive experimental analysis for heart disease prediction using artificial intelligence techniques by D. Rohan, G. Pradeep Reddy, Y. V. Pavan Kumar, K. Purna Prakash, Ch. Pradeep Reddy

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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…These results offer insights into H pylori infection risk factors and model performance.ConclusionThe Extra Trees classifier exhibited the optimal performance in predicting H pylori infections among the evaluated models. …”
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Norma i „wolność" formy sonetowej oraz „ryzyko wolności". (Przykład twórczości kilku poetów współczesnych - belgijskich i polskich) by Regina Lubas-Bartoszyńska

“…<span>Taking into account a few sonnets by two of the twentieth-century Belgian poets and four Polish ones, this paper aims to examine the accomplishment of the sonnets and the freedom of such accomplishment, which is typical of normativism: normativism which increases the risk of classifying this poetic form as sonnet. Reflecting on the greatness of the risk involved in writing this type of poetry in the twentieth century results in distinguishing three levels of the risk: the risk of interpreting the sonnet as a fixed poetic form in view of the pervasiveness of free verse taken as parody, the risk of the second level operating within the genre (breaking the rules of the literary genre), and the risk of the third and deepest level - imbuing the lyric form with extra-poetic and extra-literary elements. …”
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SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…After feature selection, our novel SCM-DL deep learning classifier model (apart from the architectures in literature, this model is constructed internally with parallel layers and carries a combinatorial layer that is beyond the combination of existing techniques) is applied and compared with Random Forest, Decision Tree, Extra Tree, and Support Vector Classifiers. …”
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An Intelligent Approach for Early and Accurate Predication of Cardiac Disease Using Hybrid Artificial Intelligence Techniques by Hazrat Bilal, Yibin Tian, Ahmad Ali, Yar Muhammad, Abid Yahya, Basem Abu Izneid, Inam Ullah

“…The proposed model is a combination of two powerful ensemble ML models, namely ExtraTreeClassifier (ETC) and XGBoost (XGB), resulting in a hybrid model named ETCXGB. …”
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Prediction of Train Arrival Delay Using Hybrid ELM-PSO Approach by Xu Bao, Yanqiu Li, Jianmin Li, Rui Shi, Xin Ding

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Toward an Accurate Liver Disease Prediction Based on Two-Level Ensemble Stacking Model by Marghany Hassan Mohamed, Botheina Hussein Ali, Ahmed Ibrahim Taloba, Ahmad O. Aseeri, Mohamed Abd Elaziz, Shaker El-Sappagah, Nora Mahmoud El-Rashidy

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Discriminator-free adversarial domain adaptation with information balance by Hui Jiang, Di Wu, Xing Wei, Wenhao Jiang, Xiongbo Qing

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Machine-Learning-Based Biomechanical Feature Analysis for Orthopedic Patient Classification with Disc Hernia and Spondylolisthesis by Daniel Nasef, Demarcus Nasef, Viola Sawiris, Peter Girgis, Milan Toma

“…The second task further classifies patients into three groups: Normal, Disc Hernia, and Spondylolisthesis (3C). …”
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Dual attention mechanisms with patch-level significance embedding for ischemic stroke classification in brain CT images by Mahesh Anil Inamdar, Anjan Gudigar, U. Raghavendra, Massimo Salvi, Nithin Raj, J. Pooja, Ajay Hegde, Girish R. Menon, U. Rajendra Acharya

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Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning by Gang Xiang, Kun Tian

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Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

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Explainable machine learning models for mortality prediction in patients with sepsis in tertiary care hospital ICU in low- to middle-income countries by Saumya Diwan, Vinay Gandhi, Esha Baidya Kayal, Puneet Khanna, Amit Mehndiratta

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Early detection of bloodstream infection in critically ill children using artificial intelligence by Hye-Ji Han, Kyunghoon Kim, June Dong Park

“…Algorithms compared were extra trees, random forest, light gradient boosting, extreme gradient boosting, and CatBoost. …”
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Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

“…The ensemble learning algorithms used include AdaBoost (AD), Gradient Boosting Classifier (GBM), Random Forest (RF) and Extra Trees (ET). …”
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Early diagnosis of autism across developmental stages through scalable and interpretable ensemble model by Nasirul Mumenin, Maisha Mumtaz Rahman, Mohammad Abu Yousuf, Farzan M. Noori, Md Zia Uddin

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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

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