Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

“…Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. …”
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Enhancing Creativity and Validation in Explanatory Deep Learning-Based Symbolic Music Generation: A Hybrid Approach With LSTM and Genetic Algorithms by Ahmad Zainul Fanani, Arry Maulana Syarif, Ika Novita Dewi, Abdul Karim

“…This research proposes an explanatory deep learning-based music generation approach, where the output of a deep learning model is validated through a set of predefined musical rules, with a refinement process applied when inaccuracies are detected. …”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

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Research on Recommendation Model Based on Multi-round Dialogue of Large Language Model by CHANG Baofa, CHE Chao, LIANG Yan

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Unpacking research on computational thinking in mathematics education: A systematic literature review by Cut Morina Zubainur, Cut Rina Rossalina, Muhammad Subianto, Dwi Fadhiliani

“…The findings show that CT strongly supports students’ problem-solving skills, particularly through Project-Based Learning (PjBL), which fosters engagement, collaboration, and algorithmic thinking. Geometry and statistics emerged as the most effective topics for developing CT, as they promote decomposition, pattern recognition, and abstraction skills aligned with junior high school cognitive development. …”
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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

“…Next, the main techniques in sequential recommendation are summarized in detail, including: traditional methods based on Markov chains, which model user behavior sequences by relying on state transition probabilities; deep learning-driven methods, which utilize neural network models to capture long-term dependencies and complex patterns; hybrid models, which combine multiple algorithms to enhance the accuracy and robustness of recommendation systems; and emerging methods based on large language models, which improve the understanding of user behavior and recommendation content through the integration of pre-trained large language models. …”
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Research on Methods for the Recognition of Ship Lights and the Autonomous Determination of the Types of Approaching Vessels by Xiangyu Gao, Yuelin Zhao

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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…This approach is considered a hybrid of optimization algorithms and classifiers in machine learning. Binary Whale Optimization (BWO) and Binary Grey Wolf Optimization (BGWO) algorithms are used for feature selection and K-Nearest Neighbor (KNN) and Fuzzy K-Nearest Neighbor (FKNN) algorithms are applied as the classifiers in this research. …”
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Research on Grouting Dynamic Monitoring Based on Borehole–Tunnel Joint Resistivity Method by Cheng Wang, Lei Zhou, Liangjun Yan, Bofan Li

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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

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Cognitive load assessment through EEG: A dataset from arithmetic and Stroop tasksMendeley Data by Ali Nirabi, Faridah Abd Rahman, Mohamed Hadi Habaebi, Khairul Azami Sidek, Siti Yusoff

“…The proposed dataset serves as a valuable resource for advancing research in the realm of brain-computer interfaces and offers insights into identifying EEG patterns associated with stress.The proposed dataset serves as a valuable resource for researchers, offering insights into identifying EEG patterns that correlate with different stress states. …”
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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

“…To address these limitations, this research proposes three innovative hybrid models that integrate metaheuristic optimization algorithms with support vector machine (SVM): multi-verse optimizer-SVM (MVO-SVM), salp swarm algorithm-SVM (SSA-SVM), and Harris’s Hawk optimization-SVM (HHO-SVM). …”
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Cluster Sort: A Novel Hybrid Approach to Efficient In-Place Sorting Using Data Clustering by Mohit Subramaniam, Tanya Tripathi, Omkumar Chandraumakantham

“…This research work introduces a clustering-based in-place sorting algorithm, cluster sort. …”
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Microcontroller-Driven Battery Management in Hybrid Energy Systems: A Systematic Review of Applications, Control Strategies, and Emerging Trends by Ripfumelo Humphrey Malele, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…The study further identifies patterns, themes, and emerging trends in the literature, highlights research gaps, and proposes directions for future work in this field.…”
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Exploring the relationship between dietary patterns and health-related quality of life among Iranian adult population: Tehran lipid and glucose study by Mahdieh Niknam, Somayeh Hosseinpour-Niazi, Sara Jalali-Farahani, Parisa Amiri, Parvin Mirmiran, Firoozeh Hosseini-Esfahani, Elaheh Ainy, Fereidoun Azizi

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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

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Sex differences in alcohol use patterns and related harms: A mixed-methods, cross-sectional study of men and women in northern Tanzania. by Madeline McNee, Niveditha Badrinarayanan, Eleanor Strand, Thiago Augusto Hernandes Rocha, Timothy Antipas Peter, Yvonne Sawe, Anna Tupetz, Diego Galdino França, Judith Boshe, Joao Ricardo Nickenig Vissoci, Monica H Swahn, Blandina Mmbaga, Catherine Staton

“…FGD transcripts revealed sex differences in four themes: alcohol initiation, consumption patterns, risk behaviors, and social stigma. This study identified important sex differences in the manifestation of AUD in northern Tanzania with respect to alcohol initiation, consumption patterns, risk behavior, and stigma. …”
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The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China by Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Gu

“…This study aims to investigate the distribution patterns of bird species in urban built-up areas and their impact factors from multiple dimensions, including spatiotemporal distribution, environmental changes, and anthropogenic disturbances, as well as overall distribution and local hotspots. …”
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QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…Quasi-periodic patterns (QPPs) are prominent spatiotemporal brain dynamics observed in functional neuroimaging data, reflecting the alternation of high and low activity across brain regions and their propagation along cortical gradients. …”
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REVIEW OF: GOLUBKOVA O.N. FUNDAMENTALS OF SCIENTIFIC RESEARCH IN THE PROFESSIONAL FIELD: TEXTBOOK by A.A. Bilyalova, A.N. Utekhina

“…This review examines the contents of an electronic textbook ‘Fundamentals of Scientific Research in the Professional Field’ by O.N. Golubkova, Candidate of Pedagogy, Associate Professor. …”
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