Non-ST segment elevation myocardial infarction: results of 2021−2022 by O. L. Barbarash, V. V. Kashtalap

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Problematic aspects of staffing the domestic pharmacy segment in the context of pharmaceutical safety by N. O. Tkachenko, O. B. Pankevych, B. P. Hromovyk

“…The aim of the work is to identify problematic issues of human resource potential in the domestic pharmacy segment from the point of view of pharmaceutical safety. …”
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Detecting and Estimation Change-point in Dynamic Systems using Segmentation Technique by Thafer Ramathan Muttar AL-Badrany, Najlaa Saad Abraham Al-Sharaby

“…Discovery points of changing and estimation it is one of the critical issues, and in this research we use package of statistical and engineering criterion used in the discovery and estimation of the change points. …”
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DIGITAL FINANCIAL ASSETS: SEGMENTS AND PROSPECTS OF LEGAL REGULATION IN THE BRICS COUNTRIES by I. Sarnakov

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From Gene to Clinic: The Role of APOL1 in Focal Segmental Glomerulosclerosis by Charlotte Delrue, Marijn M. Speeckaert

“…Apolipoprotein L1 (<i>APOL1</i>) genetic variations, notably the G1 and G2 alleles, have important roles in the pathophysiology of focal segmental glomerulosclerosis (FSGS) and other kidney problems, especially in people of African descent. …”
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Analysis of breast cancer classification and segmentation techniques: A comprehensive review by Malaya Kumar Nath, Kohilavani Sundararajan, Shanmathi Mathivanan, Bhagyashree Thandapani

“…This study identifies ongoing issues essential for driving future advancements in BC detection and segmentation to improve clinical outcomes.…”
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Application of ResUNet-CBAM in Thin-Section Image Segmentation of Rocks by Ling Zhao, Huili Zhang, Xianda Sun, Zhaozhuo Ouyang, Chengwu Xu, Xudong Qin

“…To address these issues, this paper proposes a novel segmentation algorithm based on an improved UNet network, integrating residual networks and the CBAM attention mechanism. …”
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Research on Intelligent Detection and Segmentation of Rock Joints Based on Deep Learning by Lei Peng, Haibo Wang, Chun Zhou, Feng Hu, Xiaoyang Tian, Zhu Hongtai

“…The current methods for detecting joints on tunnel face rely primarily on manual sketches, which are associated with issues of low detection efficiency and subjectivity. …”
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Parallel robotic automated docking method for realizing space segment assembly by Deyuan Sun, Ruihan Xu, Junyi Wang, Zhigang Xu, Runan Cao

“…Abstract Assembling large, heavy space segments presents a significant challenge in aerospace engine production. …”
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Intelligent cell images segmentation system: based on SDN and moving transformer by Jia Wu, Yao Pan, Qing Ye, Jing Zhou, Fangfang Gou

“…This study aims to develop an intelligent system to enhance the diagnostic accuracy of cytopathology images by addressing image noise and segmentation issues, thereby improving the efficiency of medical professionals in disease diagnosis. …”
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Bank Customer Segmentation and Marketing Strategies Based on Improved DBSCAN Algorithm by Xiaohua Yan, Yufeng Li, Fuquan Nie, Rui Li

“…It also highlights the limitations of the traditional DBSCAN algorithm, including issues with parameter selection and a lack of diverse clustering metrics. …”
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Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging by Anh T. Tran, Tal Zeevi, Seyedmehdi Payabvash

“…The technical strategies summarized in this review can enhance the robustness and generalizability of deep learning models for segmentation and classification to improve their reliability for real-world clinical practice.…”
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Enhancing Road Scene Segmentation With an Optimized DeepLabV3+ by Zhe Ren, Libao Wang, Tianming Song, Yihang Li, Jian Zhang, Fengfeng Zhao

“…To address these issues, this paper proposes an enhanced road scene segmentation method based on DeepLabV3+ that addresses the common trade-offs between accuracy and real-time performance in existing approaches. …”
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Federated learning with integrated attention multiscale model for brain tumor segmentation by Sherly Alphonse, Fidal Mathew, K. Dhanush, V. Dinesh

“…However, traditional brain tumor segmentation techniques usually rely on centralized data storage and analysis, which might result in privacy issues and violations. …”
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Multilevel Feature Interaction Network for Remote Sensing Images Semantic Segmentation by Hongkun Chen, Huilan Luo

“…These characteristics render existing methods ineffective in accurately segmenting small targets and prone to boundary blurring. …”
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A highly generalized federated learning algorithm for brain tumor segmentation by Jun Wen, Xiusheng Li, Xin Ye, Xiaoli Li, Hang Mao

“…Such data exhibit non-independent, non-identically distributed characteristics, which adversely affect segmentation accuracy and generalizability. To address these issues, this paper proposes a client-side brain tumor image segmentation model utilizing Virtual Adversarial Training (VAT) integrated into a 3D U-Net to improve model performance under conditions of limited datasets, effectively addressing data scarcity and imbalance within the federated learning environment by optimizing the use of brain tumor image data held by each client. …”
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Semantic Co-Occurrence and Relationship Modeling for Remote Sensing Image Segmentation by Yinxing Zhang, Haochen Song, Qingwang Wang, Pengcheng Jin, Tao Shen

“…However, RS semantic segmentation is hindered by issues like class imbalance, occlusion, blurring, and small target sizes. …”
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Medical Image Segmentation for Anomaly Detection Using Deep Learning Techniques by Bibat Thokar, Binod Sapkota, Babu R. Dawadi, Shashidhar R. Joshi

“…Medical images are the standard approach for the analysis and diagnosis of critical issues of diseases. To minimize the time-consuming inspection and evaluation process of the medical images from physicians in diagnosis, an automatic segmentation mechanism of abnormal features in medical images is required. …”
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RMP-UNet: An Efficient and Lightweight Model for Apple Leaf Disease Segmentation by Wenbo Zhao, Lijun Hu, Qi Wang, Hongxin Wu, Jiangbo Wang, Xu Li, Cuiyun Wu

“…To address these issues, this study proposes RMP-UNet, an efficient and lightweight model for apple leaf disease segmentation. …”
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Adaptive Select Loss Strategy for Semantic Segmentation of Agricultural Crop Images by Corneliu Florea, Laura Florea, Mihai Ivanovici

“…We address the problem of agricultural image segmentation by introducing a novel loss formulation called Adaptive Select Loss (ASL), inspired by the Top-k loss strategy. …”
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