PEYOLO a perception efficient network for multiscale surface defects detection by Xun Li, Yuzhen Zhao, Xiangke Jiao, Qingzhe Meng, Zhun Guo, Ruijuan Yao, Yaqiao Yang, Baoxi Yuan

“…First, we introduce the Defect Capture Path Aggregation Network, which enhances the feature fusion network’s ability to learn multi-scale representations. Second, we design a Perception-Efficient Head (PEHead) to effectively mitigate local aliasing issues, thereby reducing the occurrence of missed detections. …”
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Mine hoisting steel wire rope surface damage image recognition based on improved YOLOv8n by MAO Qinghua, YANG Fan, WANG Chao, TONG Xuyao, TONG Junwei, ZHANG Xuhui, XUE Xusheng

“…The Multi-Scale Attention Module (MSAM) was introduced into the YOLOv8n backbone network to enhance the model’s ability to distinguish between damage features and oil stain backgrounds, improving its anti-interference capability. …”
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Irregularly Sampled Time Series Interpolation for Detailed Binary Evolution Simulations by Philipp M. Srivastava, Ugur Demir, Aggelos Katsaggelos, Vicky Kalogera, Shamal Lalvani, Elizabeth Teng, Tassos Fragos, Jeff J. Andrews, Simone S. Bavera, Max Briel, Seth Gossage, Konstantinos Kovlakas, Matthias U. Kruckow, Camille Liotine, Kyle A. Rocha, Meng Sun, Zepei Xing, Emmanouil Zapartas

“…One element that is still missing from these codes is the ability to generate the complete time evolution of binaries with arbitrary initial conditions using precomputed three-dimensional grids of binary sequences. …”
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Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned by Marketa Ciharova, Khadicha Amarti, Ward van Breda, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Xianhua Peng, Mieke Schulte, Mieke Schulte, Eirini Karyotaki, Eirini Karyotaki, Eirini Karyotaki, Pim Cuijpers, Pim Cuijpers, Pim Cuijpers, Heleen Riper, Heleen Riper

“…However, investigation of algorithms detecting stress severity on a continuous scale is missing due to high demands on data quality for such analyses. …”
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Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images by Kousar Ramezani, Maryam Tofangchiha

“…The current strategies for screening of patients for oral premalignant and malignant lesions unfortunately miss a significant number of involved patients. Optical coherence tomography (OCT) is an optical imaging modality that has been widely investigated in the field of oncology for identification of cancerous entities. …”
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A Sociological study of the Relationship between Smartphone Addiction and Phubbing Case Study18-29 Year Old Females of Ramhormoz City by Ali Boudaghi, Ali Hossein Hosseinzadeh, Sayedeh Sara Mousavi Moghadam

“…The phubbing phenomenon: A cross-sectional study on the relationships among social media addiction, fear of missing out, personality traits, and phubbing behavior. …”
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Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm by M. O. Zelenskih, A. E. Saprygin, S. S. Tamozhnikov, P. D. Rudych, D. A. Lebedkin, A.  N. Savostyanov

“…These days, the ability to predict the result of the development of the system is the guarantee of the successful functioning of the system. …”
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Predicting Deep Venous Thrombosis Using Artificial Intelligence: A Clinical Data Approach by Aurelian-Dumitrache Anghele, Virginia Marina, Liliana Dragomir, Cosmina Alina Moscu, Mihaela Anghele, Catalin Anghel

“…Most importantly, the model’s high recall underscores its ability to identify nearly all true deep venous thrombosis cases, significantly reducing the risk of false negatives—a critical concern in clinical settings, where delayed or missed diagnoses can result in life-threatening complications. …”
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Validation and three years of clinical experience in using an artificial intelligence algorithm as a second read system for prostate cancer diagnosis—real-world experience by Juan Carlos Santa-Rosario, Erik A. Gustafson, Dario E. Sanabria Bellassai, Phillip E. Gustafson, Mariano de Socarraz

“…Methods: To address these challenges, this study investigates the ability of artificial intelligence (AI) to enhance diagnostic accuracy. …”
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Effect of Early Treatment of Spasticity After Stroke on Motor Recovery: Protocol for the Baclotox Multicenter, Double-Blind, Double-Dummy Randomized Controlled Trial by Emmeline Montane, Nabila Brihmat, Camille Cormier, Claire Thalamas, Vanessa Rousseau, Gerard Tap, Xavier De Boissezon, Evelyne Castel-Lacanal, Philippe Marque

“…Spasticity, functional abilities, activities of daily living, pain, and quality of life are also evaluated. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…Firstly, to enhance the ability to capture multi-dimensional features of wood surface defects and reduce information loss, a fully dynamic convolution (ODConv) is introduced. …”
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Directed attenuation to enhance vaccine immunity. by Rustom Antia, Hasan Ahmed, James J Bull

“…Early methods of attenuation were hit-and-miss, now much improved by genetic engineering. However, even current methods operate on the principle of genetic harm, reducing the virus's ability to grow. …”
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Quality Control Automation for Student Driven Digitization Workflows by Corinne Chatnik, James Gaskell

“…Many of these errors are difficult to catch during quality control checks because they are so minute, such as a missed counted page number here, or a transposed character in a filename there. …”
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VMMCD: VMamba-Based Multi-Scale Feature Guiding Fusion Network for Remote Sensing Change Detection by Zhong Chen, Hanruo Chen, Junsong Leng, Xiaolei Zhang, Qi Gao, Weiyu Dong

“…Finally, the Multi-scale Feature Guiding Fusion (MFGF) module is developed, which strengthens the global modeling ability of VMamba. Additionally, it enriches the interaction among multi-scale features to address the common issue of missed detections in changed areas. …”
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Training a convolutional neural network for exoplanet classification with transit photometry data by Juliana Wang

“…These results highlight the model’s strengths and areas for improvement; while it excels at identifying false positives (low miss rate of 5%), its higher miss rate for the ‘CONFIRMED’ class (40%) suggests a need for better detection of true exoplanets. …”
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ASSISTED REPRODUCTIVE TECHNOLOGIES FOR FERTILITY PRESERVATION OF CANCER PATIENTS by M. V. Kiseleva, E. V. Abakushina, A. F. Tsyb

“…If this happens, cancer patients may miss the only opportunity they have to preserve their ability to have a biological child. …”
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Four microcolumn agglutination anti-human globulin cards in unexpected antibody screening results: a comparative analysis by SONG Ke, MA Chunya, FU Lihui, XIAO Pan, SHI Hongmei, YU Yang

“…[Objective] To analyze the detection ability of one imported and three domestic microcolumn agglutination anti-human globulin cards in unexpected antibody screening test. …”
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Diagnostic performance of MUAC and MUACZ in screening acute malnutrition among children aged 6–23 months in Amhara Region, Ethiopia by Yonatan Menber, Tefera Belachew, Netsanet Fentahun

“…In the Receiver Operating Characteristics curve analysis, significant predictive ability was only observed with MUAC when screening global acute malnutrition cases, and it showed a poor predictive ability (AUC = 0.61, 95% CI: 0.53, 0.70) (p < 0.001). …”
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An empirical method to identify breaking waves by Mauricio Felga Gobbi

“…The method proved itself accurate for most cases, and only misses when waves are on the verge of breaking.…”
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Molecular Imaging of Autoimmune Diseases and Inflammation by S. Anna Sargsyan, Joshua M. Thurman

“…Molecular imaging methods have the potential to improve our ability to detect and characterize tissue inflammation. …”
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