Combined clinical and MRI-based radiomics model for predicting acute hematologic toxicity in gynecologic cancer radiotherapy by Lumeng Luo, Lumeng Luo, Jiahao Wang, Jiahao Wang, Hongling Xie, Hongling Xie, Bingxin Chen, Bingxin Chen, Hui Wang, Hui Wang, Qiu Tang, Qiu Tang

“…Feature selection was performed using LASSO and random forest algorithms, followed by comparison across multiple classification models. …”
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Blockchain Approach for Healthcare Using Fog Topology and Lightweight Consensus by Aya Laouamri, Sarra Cherbal, Yacine Mosbah, Chahrazed Benrebbouh, Kamir Kharoubi

“…The architecture and algorithms for signature generation, encryption, emergency state actions and consensus are developed and evaluated through extensive simulations using the NS3 toolkit.Results: The simulation results validate the effectiveness of the proposed approach in improving healthcare IoT systems. …”
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Australian Dentists' Knowledge of the Consequences of Interpretive Errors in Dental Radiographs and Potential Mitigation Measures by Shwetha Hegde, Shanika Nanayakkara, Stephen Cox, Rajesh Vasa, Jinlong Gao

“…The study also suggests further research into the role of machine learning algorithms in reducing interpretive errors in dentistry.…”
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White Blood Cell Detection Based on FBDM-YOLOv8s by Borui Sun, Xiangsuo Fan, Jie Meng, Jinfeng Wang, Huajin Chen, Lei Liu

“…The FBDM-YOLOv8s significantly outperforms other advanced object detection algorithms in terms of performance, with a 2.1% increase in mAP compared to the baseline YOLOv8s.We will release the source code on <uri>https://github.com/SSRR-LLL/FBDM-YOLOv8.git</uri>.…”
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Laser Fabrication of Multi‐Dimensional Perovskite Patterns with Intelligent Anti‐Counterfeiting Applications by Xiangyu Xu, Shoufang Liu, Yan Kuai, Yuxuan Jiang, Zhijia Hu, Benli Yu, Siqi Li

“…The combination of deep learning algorithms and a non‐deterministic manufacturing process provides a convenient means of identification and creates unclonable features. …”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

“…In response to the insufficient recognition performance and poor generalization capacity of existing detection algorithms under unstructured orchard scenarios, we constructed a customized apple image dataset captured under varying illumination conditions and introduced an improved detection architecture, YOLO11-ARAF, derived from YOLO11. …”
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Psychogenic overeating: problems of classification, diagnosis, approaches to psychotherapy (literature review) by T. A. Karavaeva, M. V. Fomicheva

“…It is noted, that it is promising to develop algorithms for diagnostics and therapy of the described nosology, the feasibility of identifying individual targets of psychotherapeutic interventions to create personalized complex programs that increase the effectiveness of therapy in relation to immediate and long-term results.…”
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Fiber Sensing in the 6G Era: Vision Transformers for <i>ϕ</i>-OTDR-Based Road-Traffic Monitoring by Robson A. Colares, Leticia Rittner, Evandro Conforti, Darli A. A. Mello

“…Backscattered traces are consolidated into space–time matrices, illustrating traffic patterns and enabling analysis through image processing algorithms. The ground truth is established by traffic parameters obtained by processing video camera images monitoring the same street using the YOLOv8 model. …”
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Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog by Dhayaa Anbajagane, M. Tabbutt, J. Beas-Gonzalez, B. Yanny, S. Everett, M. R. Becker, M. Yamamoto, E. Legnani, J. De Vicente, K. Bechtol, J. Elvin-Poole, G. M. Bernstein, A. Choi, M. Gatti, G. Giannini, R. A. Gruendl, M. Jarvis, S. Lee, J. Mena-Fernández, A. Porredon, M. Rodriguez-Monroy, E. Rozo, E. S. Rykoff, T. Schutt, E. Sheldon, M. A. Troxel, N. Weaverdyck, V. Wetzell, M. Aguena, A. Alarcon, S. Allam, A. Amon, F. Andrade-Oliveira, D. Brooks, A. Carnero Rosell, J. Carretero, C. Chang, M. Crocce, L. N. da Costa, M. E. S. Pereira, T. M. Davis, S. Desai, H. T. Diehl, S. Dodelson, P. Doel, A. Drlica-Wagner, A. Ferté, J. Frieman, J. García-Bellido, E. Gaztanaga, D. Gruen, G. Gutierrez, W. G. Hartley, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. Huterer, D. J. James, E. Krause, K. Kuehn, O. Lahav, J. L. Marshall, R. Miquel, J. Muir, J. Myles, A. Pieres, A. A. Plazas Malagón, J. Prat, M. Raveri, S. Samuroff, E. Sanchez, D. Sanchez Cid, I. Sevilla-Noarbe, M. Smith, E. Suchyta, G. Tarle, D. L. Tucker, A. R. Walker, P. Wiseman, Y. Zhang, The DES Collaboration

“…Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. …”
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Chlormethine Gel for Treatment of Patients with Mycosis Fungoides: Best Practices and Guidance to Clinicians by Larisa Geskin, Christiane Querfeld, Emmilia Hodak, Neda Nikbakht, Evangelia Papadavid, Marco Ardigò, Ulrike Wehkamp, Martine Bagot

“…While multiple guidelines provide treatment recommendations, there are currently no clear treatment algorithms for MF. Chlormethine gel is recommended by major treatment guidelines as a first-line option for stage IA–IIA disease, and, on the basis of these guidelines, used in combination with other therapies in patients with advanced-stage MF in clinical practice. …”
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Integrating IT and OT for Cybersecurity: A Stochastic Optimization Approach via Attack Graphs by Gonzalo Martinez Medina, Krystel K. Castillo-Villar, Tanveer Hossain Bhuiyan

“…A hybrid solution approach that integrates the Sample Average Approximation (SAA) and Benders Decomposition (BD) algorithms is used to efficiently solve the resulting large-scale problem. …”
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PIPNet: A Deep Convolutional Neural Network for Multibaseline InSAR Phase Unwrapping Based on Pure Integer Programming by Hui Liu, Ke Zheng, Changwei Miao, Xuemei Liu, Xianlin Liu, Lin Li, Yongguang Zhang, Longhai Xiong

“…Theoretical analysis and two experimental results indicate that PIPNet-PU has much lower execution time than MCF, cluster analysis, and two-stage programming approach algorithms, and the second-best unwrapping accuracy for short-baseline interferogram and the best unwrapping ability for long-baseline interferogram. …”
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Key aspects of preparing future physical education and sports specialists to provide pre-medical care by Maramukha Natalia, Tyshchenko Valeria

“…Special attention is paid to the analysis of scientific publications that describe the algorithms for teaching students actions in various emergency situations. …”
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The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features by H. Müller Schmied, H. Müller Schmied, T. Trautmann, S. Ackermann, D. Cáceres, M. Flörke, H. Gerdener, E. Kynast, T. A. Peiris, L. Schiebener, M. Schumacher, P. Döll, P. Döll

“…In this paper, the refinements, new algorithms, and new data of the most recent model version v2.2e are described, together with a thorough evaluation of the simulated water use, streamflow, and terrestrial water storage anomaly against observation data. …”
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FOPID-Controlled Self-Propelled Pipeline Inspection Robot for Internal Mapping of Small-Diameter Pipelines by Rizwan Aziz Mangi, Ghulam E. Mustafa Abro, Sufyan Ali Memon, Aneela Pathan, Khalil Muhammad Zuhaib, Maran Marimuthu

“…This research facilitates the development of a novel category of economical, compact, and intelligent PIRs that can enhance sophisticated mapping algorithms. Its applicability encompasses several industrial inspection and maintenance contexts, enhancing the safety and efficiency of pipeline infrastructure management.…”
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Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
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Beyond Digital Literacy: Building Youth Digital Resilience Through Existing “Information Sensibility” Practices by Amelia Hassoun, Ian Beacock, Todd Carmody, Patrick Gage Kelley, Beth Goldberg, Devika Kumar, Laura Murray, Rebekah Su Park, Behzad Sarmadi, Sunny Consolvo

“…Participants generally algorithmically encountered (rather than searched for) information online, and their engagement was shaped more by social motivations—like belonging—than truth seeking. …”
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A multi-cohort validated OXPHOS signature predicts survival and immune profiles in grade II/III glioma patients by Jun Mou, Min Zhang, Fumin Qin, Yajie Cui, Keyou Xu, Baoye Pang, Xinyue Li, Wanyi Tan, Aiqi Yang, Yaxin Liu, Lingjun Shen, Yanting Liu, Kai Xu

“…The immune cell composition and tumor microenvironment (TME) characteristics were assessed using ESTIMATE, MCPcounter, and CIBERSORT algorithms. Based on prognostic DEGs, we constructed a four-gene prognostic signature (MAOB, IGFBP2, SERPINA1, and LGR6).ResultsThe C2 molecular subtype was associated with poorer prognosis, higher immune scores, and enrichment in tumor-promoting pathways. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

“…We ranked differentially expressed genes (DEGs) using feature-weighting algorithms, such as Relief and kernel-based methods, to model expression patterns between sensitive and tolerant cultivars. …”
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