Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

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Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…In this paper, we analyze the multi-intelligence application architecture in power load forecasting, and analyze the function of each intelligent unit applied to short-term power load forecasting; based on clarifying the interaction relationship of each intelligent unit in short-term power load forecasting, we model short-term power load forecasting as a distributed and partially observable Markov decision-making process, which is suitable for multi-intelligence deep reinforcement learning; based on the MATD3 algorithm, a centralized training-distributed execution framework is used to train multiple intelligences within the model to achieve short-term power load forecasting. …”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…This paper focuses on forecasting models using T-SFIS, GBMBoost, and Decision Tree, combined with metaheuristic algorithms (GWO, QPSO) in hybrid and ensemble frameworks. …”
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Artificial intelligence and robotic surgery in clinical medicine: progress, challenges, and future directions by Salih Beyaz, Alaaddin Levent Özgözen, Necmettin Turgut, Hakkı Can Ölke

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SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS by Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

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Efficient Equivalence Checking Technique for Some Classes of Finite-State Machines by Vladimir A. Zakharov

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Convolutional Neural Network-Based Low Light Image Enhancement Method by M.X. Li, C.J. Xu

“…In this study, a new remote sensing image recognition model is proposed by combining the filtering algorithm to reconstruct the time series curve, fusing the quadratic difference method and decision tree, and introducing the morphological similarity distance method. …”
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The use of rough rules in the selection of topographic objects for generalizing geographical information by Fiedukowicz Anna

“…The conducted research indicates the advantage of the DRST and RST approaches (with the CN2 algorithm) due to the quality of the obtained selection, the greater simplicity of the decision system, and better refined IT tools enabling the use of these systems. …”
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Immunophenotype-guided interpretable radiomics model for predicting neoadjuvant anti-PD-1 response in stage III–IV d-MMR/MSI-H colorectal cancer by Xuan Zhang, Zhenhui Li, Yiwen Zhang, Yanli Li, Xi Zhong, Wenjing Jiang, Xiaobo Chen, Zaiyi Liu, Liebin Huang, Caixia Zhang, Lizhu Liu, Ruimin You, Xiaoping Yi

“…Eventually, an interpretable immunotherapy response prediction model was developed by integrating a decision tree algorithm with SHapley Additive exPlanations (SHAP) analysis.Results Two immunophenotypes (immune-hot and immune-cold) were identified, compared with the immune-cold, the former exhibited more abundant RNA-based immune cell infiltration and higher densities of CD3 and CD8 T cells in both the core tumor and invasive margin areas. …”
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Trustworthy Load Prediction for Cantilever Roadheader Robot Without Imputation by Pengjiang Wang, Yuxin Li, Yunwang Li, Yang Shen, Weixiong Zheng, Shigen Fu

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Using Artificial Intelligence Tools to Analyze Particulate Matter Data (PM_2.5) by Miriam Gómez Marín, Henry O. Sarmiento-Maldonado, Alba Nelly Ardila Arias, William Alonso Giraldo Aristizábal, Rubén Darío Vásquez-Salazar

“…A multivariable clustering methodology was evaluated using the LAMDA algorithm as an alternative tool for analyzing air quality data. …”
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A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

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Forecasting Delivery Time of Goods in Supply Chains Using Machine Learning Methods by V. K. Rezvanov, O. M. Romakina, E. V. Zaytseva

“…The basic algorithm for the delivery forecasting model was the Decision Tree algorithm. …”
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An Inverse Modeling Multi-Objective Optimization Technique Based on Incremental Learning and Fuzzy Clustering by Gadallah Mohamed Abd Elaziz, Yasmine Abouelseoud, Sara H. Kamel

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Optimizing Aircraft Routes in Dynamic Conditions Utilizing Multi-Criteria Parameters by Oleh Sydorenko, Nataliia Lysa, Liubomyr Sikora, Roman Martsyshyn, Yuliya Miyushkovych

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Research on the deformation prediction model of surrounding rock based on SSA-VMD-GRU by Xiao Jiming, Guo Hongyan, Guo Huajun, Hu Juyi, Zhang Zhongzhe

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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles by Pengcheng Ma, Shuai Zhang, Bin Zhou, Wenqi Shao, Haowen Li, Tengfei Ma, Dong Guo

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Development of data driven models to accurately estimate density of fatty acid ethyl esters by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H. S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Abdolali Yarahmadi Kandahari

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Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy by Barbara Pękala, Dawid Kosior, Wojciech Rząsa, Katarzyna Garwol, Janusz Czuma

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