DMRIntTk: Integrating different DMR sets based on density peak clustering. by Wenjin Zhang, Wenlong Jie, Wanxin Cui, Guihua Duan, You Zou, Xiaoqing Peng

“…In DMRIntTk, the genome is segmented into bins, and the reliability of each DMR set at different methylation thresholds is evaluated. Then, the bins are weighted based on the covered DMR sets and integrated into final DMRs using a density peak clustering algorithm. …”
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Building an Otoscopic screening prototype tool using deep learning by Devon Livingstone, Aron S. Talai, Justin Chau, Nils D. Forkert

“…The aim of this work was to develop and evaluate an automatic software prototype to identify otologic abnormalities using a deep convolutional neural network. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Each segmentation was evaluated for phenotypic homogeneity, separation, and clinical use. …”
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Power Grid Clock Synchronization Optimization Based on Stackelberg Game Theory by Jiahao Li, Yitao Zhao, Yiming Zhang, Zhiyu Xia, Chuanxu Chen, Quansheng Guan

“…Furthermore, the network simulator Mininet and the open-source software-defined network framework Ryu are used to evaluate the performance of the proposed method. Compared with the bandwidth reservation scheme, our proposed method is more suitable for differentiated clock synchronization of resource-limited new energy power networks. …”
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Population-Level Cell Trajectory Inference Based on Gaussian Distributions by Xiang Chen, Yibing Ma, Yongle Shi, Yuhan Fu, Mengdi Nan, Qing Ren, Jie Gao

“…CPvGTI utilizes a Gaussian mixture model, optimized by the Expectation–Maximization algorithm, to construct new cell populations in the original data space. …”
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DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding by Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh

“…Backpropagation is the foremost prevalent and common algorithm for training conventional neural networks with deep construction. …”
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Eosinophilic Fasciitis: A Review of Research and Therapeutic Possibilities by Julia Biernikiewicz, Anna Wilewska, Bartosz Pomirski, Agata Pomirska, Milena Biernikiewicz, Konstanty Alabrudziński, Agnieszka Borowiec, Kinga Borowiec, Paulina Kwaśniewska, Patryk Graczyk

“…Given the rarity and complexity of EF, the study also seeks to clarify its differentiation from similar diseases and offer insights into effective therapies for early diagnosis and improved treatment outcomes. …”
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THE OBJECTIFICATION OF THE PRINCIPLE OF FAIRNESS IN TAX LAW OF RUSSIA IN THE ASPECT OF ANALYSIS OF RECENT LEGISLATIVE DEVELOPMENTS by M. Koilova

“…We also analyzed the modified algorithm of taxation of citizens' property and noted the problems of its practical approbation. …”
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Active Traffic Sensor Location Problem for the Uniqueness of Path Flow Identification in Large-Scale Networks by Ahmed Almutairi, Mahmoud Owais

“…Therefore, finding an efficient solution algorithm for large-scale networks is challenging. …”
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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…This paper presents a novel algorithm that leverages cutting-edge machine-learning techniques to accurately and efficiently detect AI-generated texts. …”
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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

“…On the other hand, existing SSC techniques fail to differentiate between the varied attributes within the feature space. …”
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Riemannian Manifolds for Biological Imaging Applications Based on Unsupervised Learning by Ilya Larin, Alexander Karabelsky

“…Graph-based segmentation has a long history, e.g., the normalized cuts algorithm treated segmentation as a graph partitioning problem—but only recently have such ideas merged with deep learning in an unsupervised manner. …”
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Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…This study systematically evaluates their prognostic significance and explores their potential for therapeutic intervention in colon adenocarcinoma. …”
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CENPF as a Potential Biomarker Associated with the Immune Microenvironment of Renal Cancer by Meilin Chen MS, Xiuxin Tang MS, YanPing Liang MD, Tangdang Ding MS, Meifang He PhD, Dong Wang PhD, Ruizhi Wang PhD

“…Single-cell sequencing data from the GSE159115 dataset were analyzed, and the CIBERSORT algorithm was applied to evaluate the composition of tumor immune infiltrating cells (TIICs). …”
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The superiority of feasible solutions-moth flame optimizer using valve point loading by Mohammad Khurshed Alam, Herwan Sulaiman, Asma Ferdowsi, Md Shaoran Sayem, Md Mahfuzer Akter Ringku, Md. Foysal

“…The MFO, Grey Wolf Optimizer (GWO), Success-history-based Parameter Adaptation Technique of Differential Evolution - Superiority of Feasible Solutions (SHADE-SF), and Superiority of Feasible Solutions-Moth Flame Optimizer (SF-MFO) algorithms are applied to address the OPF problem with two objective functions: (1) reducing energy production costs and (2) minimizing power losses. …”
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Application of Artificial Intelligence Models to Predict the Onset or Recurrence of Neovascular Age-Related Macular Degeneration by Francesco Saverio Sorrentino, Marco Zeppieri, Carola Culiersi, Antonio Florido, Katia De Nadai, Ginevra Giovanna Adamo, Marco Pellegrini, Francesco Nasini, Chiara Vivarelli, Marco Mura, Francesco Parmeggiani

“…Early detection of nAMD is crucial because, if untreated, it can lead to blindness. Software and algorithms that utilize artificial intelligence (AI) have become valuable tools for early detection, assisting doctors in diagnosing and facilitating differential diagnosis. …”
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Comprehensive datasets for RNA design, machine learning, and beyond by Jan Badura, Agnieszka Rybarczyk, Tomasz Zok

“…The lack of standardized benchmark datasets further hinders the development and evaluation of these tools. To address this, we created a comprehensive dataset of over 320 thousand instances from experimentally validated sources to establish a new community-wide benchmark for RNA design and modeling algorithms. …”
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The role of LAMA5 in breast cancer progression and its potential in immunotherapy by Xiaoli Zhang, Hongfang Yan, Lihan Bie, Zheng Xu, Xiaoyang Yao, Zhilan Li, Chengshan He, Zhouhong Xiang, Xiudi Jiang

“…Immune infiltration was evaluated using CIBERSORT and ESTIMATE algorithms. …”
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PIC2O-Sim: A physics-inspired causality-aware dynamic convolutional neural operator for ultra-fast photonic device time-domain simulation by Pingchuan Ma, Haoyu Yang, Zhengqi Gao, Duane S. Boning, Jiaqi Gu

“…Recently, AI has been applied to realize orders-of-magnitude speedup in partial differential equation solving. However, AI-based FDTD solvers for photonic devices have not been clearly formulated. …”
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Multi-omics analysis of the effects of pla2g4a on the prognosis of various cancers and its experimental validation in breast cancer cell lines by Yao Qian, Quan Yuan, Hao Yu, Rongjie Ye, Ming Niu, Feng Liu

“…Methods Download cancer-related data from databases such as UCSC Xena and ExMdb, use LASSO Cox regression and various machine learning algorithms to screen genes associated with BC survival, and perform functional and pathway enrichment analysis. …”
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