Temporal trends in the incidence of adverse effects of medical treatment in BRICS countries from 1990 to 2021: an age-period cohort analysis by Xingmin Wei, Xingmin Wei, Lu Jiang, Zhidong Zhang, Longjian Shang, Kun Liu, Xiaoang Qin, Gaoheng Ding, Lu Liu, Jianjun Wu

“…To strengthen AEMT prevention, these countries should prioritize optimizing existing healthcare resources, such as workforce training and surveillance systems. …”
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Automated Video Assistant Referee in Lead Climbing by Eliane Künzler, David Roder, Urs Stöcker, Peter Wolf

“…Next, we will compare our scoring algorithm representing given regulations with scores awarded. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Abstract Background Metastatic spinal disease often leads to significant morbidity, and accurate prediction of postoperative outcomes can help optimize patient management and resource allocation. …”
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Cross-sectional imaging of speed-of-sound distribution using photoacoustic reversal beacons by Yang Wang, Danni Wang, Liting Zhong, Yi Zhou, Qing Wang, Wufan Chen, Li Qi

“…By picking up the PRB signal using a graph-based dynamic programing algorithm, we formulate a linear inverse model for pixel-wise SOS reconstruction and solve it with iterative optimization technique. …”
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Early Forest Fire Detection With UAV Image Fusion: A Novel Deep Learning Method Using Visible and Infrared Sensors by Kunlong Niu, Chongyang Wang, Jianhui Xu, Jianrong Liang, Xia Zhou, Kaixiang Wen, Minjian Lu, Chuanxun Yang

“…The results show that the improved registration method effectively aligns visible and infrared images, optimizing the fusion process and enhancing the use of multisource information. …”
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Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients by Yunjie Zhang, Songjian Tong, Junhui Yang, Jiawei Lin, Yifan Kong, Deyu Lu, Yan Chen, Yingchao Li, Linfeng Xu, Xiuyan Kong, Guoqing Zhu, Hao Zhang, Pixu Liu, Zhijie Yu, Jinglin Xia

“…Through recursive feature elimination (RFE), we systematically developed prediction models employing ten distinct ML algorithms. The SHAP algorithm was implemented to enhance model interpretability, while patient stratification was subsequently performed using PCA and K-means clustering to facilitate comprehensive prognostic analysis. …”
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Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year‐span cross‐sectional study by Jing Tan, Chunrong Liu, Min Yang, Yiquan Xiong, Shiyao Huang, Yana Qi, Meng Chen, Lehana Thabane, Xinghui Liu, Lin He, Xin Sun

“…Conclusions The use of statistical methods is not yet optimal. Ten recommendations were offered to assist the statistical methods of prognostic prediction models in obstetric care.…”
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HPV-negative oropharyngeal carcinoma as a separate prognostkally unfavorable form of cancer, requiring new approaches to treatment (case report) by A. R. Gevorkov, A. V. Boyko, A. P. Polyakov, L. V. Bolotina, N. N. Volchenko, I. V. Rebrikova, A. М. Lemeshko, S. V. Shashkov

“…HPV-negative oropharyngeal cancer requires an optimized treatment algorithm and, possibly, more aggressive therapeutic measures, such as increased radiation doses. …”
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Integration of YOLOv9 Segmentation and Monocular Depth Estimation in Thermal Imaging for Prediction of Estrus in Sows Based on Pixel Intensity Analysis by Iyad Almadani, Aaron L. Robinson, Mohammed Abuhussein

“…Many researchers focus on improving reproductive health in sows and ensuring successful breeding by accurately identifying the optimal time of ovulation through estrus detection. …”
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The joint role of the immune microenvironment and N7-methylguanosine for prognosis prediction and targeted therapy in acute myeloid leukemia by Zhixiang Chen, Zhixiang Chen, Zhimei Chen, Xiaobo Huang, Xiaobo Huang, Xiaobo Huang, Xiongbin Yan, Xiongbin Yan, Xiaolin Lai, Xiaolin Lai, Shaoyuan Wang, Shaoyuan Wang

“…In vitro CCK-8 assays validated dactolisib’s monotherapy efficacy and synergistic cytotoxicity when combined with doxorubicin in AML cells.ConclusionThe IMEm7G gene signature established in our study effectively optimized the risk classification and predicted immunotherapy response in AML. …”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

“…This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. …”
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Assessment of prostate cancer aggressiveness through the combined analysis of prostate MRI and 2.5D deep learning models by Yalei Wang, Yuqing Xin, Baoqi Zhang, Fuqiang Pan, Xu Li, Manman Zhang, Yushan Yuan, Lei Zhang, Peiqi Ma, Bo Guan, Yang Zhang

“…Further, a clinical feature model (Clinic-LightGBM) was constructed using LightGBM to include clinical information. The optimal feature model was then combined with Clinic-LightGBM to establish a nomogram. …”
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…Abstract Background Gadolinium-enhanced “sampling perfection with application-optimized contrasts using different flip angle evolution” (SPACE) sequence allows better visualization of brain metastases (BMs) compared to “magnetization-prepared rapid acquisition gradient echo” (MPRAGE). …”
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CHIP: Clustering Hotspots in Layout Using Integer Programming by Rohit Reddy Takkala, Chris Chu

“…However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. …”
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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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Efficient scheduling of multiple software projects for work continuity and identical completion time by Abdulrahman Aldhubaiban, Ali AlMatouq

“…Our continuous variable model was solved in the cloud for optimality for large instances of upto 40 different software projects and 100 employees in less than 21 min using nonlinear programming algorithms. • A continuous variable nonlinear model is developed to efficiently schedule large-scale software projects. • The model enables scheduling for multiple projects with identical completion times while ensuring work continuity. • A cloud-based program architecture is designed to facilitate the testing of multiple solvers online.…”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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Engineering and Technological Advancements in Repetitive Transcranial Magnetic Stimulation (rTMS): A Five-Year Review by Abigail Tubbs, Enrique Alvarez Vazquez

“…A structured review of peer-reviewed studies from 2019 to 2024 focused on technological and clinical advancements in rTMS, including AI-driven personalized treatments, portable devices, and integrated BCIs. AI algorithms have optimized patient-specific protocols, while portable devices have expanded access. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…The approach integrates quantum computing principles into classical control frameworks, creating a hybrid methodology that leverages quantum-inspired optimization while maintaining implementation feasibility on conventional hardware. …”
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