Classifying schizophrenia using functional MRI and investigating underlying functional phenomena by Yangyang Liu, Bi Wan, Zixuan Liu, Shuaiqi Zhang, Pei Liu, Ningning Ding, Yuxin Wang, Jun Dong, Moiz Kabeer Ahmad, Haisan Zhang

“…The Louvain community detection algorithm and structural equation modeling were used to investigate community relationships and potential causal effects. …”
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Bile acids in follicular fluid: potential new therapeutic targets and predictive markers for women with diminished ovarian reserve by Shu Ding, Wenyan Li, Xianglei Xiong, Manfei Si, Chuyu Yun, Yuqian Wang, Lixuan Huang, Sen Yan, Xiumei Zhen, Jie Qiao, Xinyu Qi

“…Then, we constructed a diagnostic model for DOR using the random forest algorithm based on five different BAs. Additionally, we performed a functional enrichment analysis on differentially expressed genes (DEGs) in GCs from both DOR and NOR patients. …”
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Security decision method for the edge of multi-layer satellite network based on reinforcement learning by Peiliang ZUO, Shaolong HOU, Chao GUO, Hua JIANG, Wenbo WANG

“…This paper uses deep reinforcement learning algorithms to implement edge security decisions for satellite networks. …”
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Disturbance types play a key role in post-disturbance vegetation recovery in boreal forests of Northeast China by Yue Yu, Zhihua Liu, Wenjuan Wang, Wenru Xu, Qiushuang Lv, Kaili Li, Wenhua Guo, Lei Fang, Qinglong Zhang, Zhiwei Wu, Bo Liu

“…Utilizing the multiple spectral indices, together with the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm, we integrally detected and attributed forest disturbances into fire, harvest, and urbanization (forest converted to urban, rural housing, road, etc.) across the Great Xing’an Mountains (GXM) of Northeast China from 1986 to 2022. …”
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Multidisciplinary Approach of a Male Case of Imported Malaria, HIV Chronic Infection, and Latent Syphilis by Rebeca Eunice García-Mendiola, Maritza Micheli García-Lucas, Jennifer Morales-Vázquez, Raúl Adrián Cruz-Flores, Miguel Ángel Loyola-Cruz, Clemente Cruz-Cruz, Emilio Mariano Durán-Manuel, Enzo Vásquez-Jiménez, Graciela Castro-Escarpulli, María de Jesús Sánchez-Guzmán, Victor Hugo Gutiérrez-Muñoz, Iliana Alejandra Cortés-Ortíz, Misael González-Ibarra, Juan Carlos Bravata-Alcántara, Jesús Alejandro Pineda-Migranas, Estibeyesbo Said Plascencia-Nieto, Carlos Alberto Jiménez-Zamarripa, Erika Gómez-Zamora, Claudia Camelia Calzada-Mendoza, Juan Manuel Bello-López

“…During the STI diagnostic algorithm, latent syphilis was detected and microscopic observation of blood smears revealed parasitic forms compatible with malaria. …”
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AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality: an AI-CVD study within the Multi-Et... by Ning Ma, Rozemarijn Vliegenthart, Matthew J Budoff, Khurram Nasir, Javier J Zulueta, Jagat Narula, Daniel Levy, Wenjun Fan, Kim Williams, David J Maron, Chenyu Zhang, Prediman K Shah, Zahi Fayad, Morteza Naghavi, Kyle Atlas, Anthony Reeves, Jakob Wasserthal, Thomas Atlas, Claudia I. Henschke, David F. Yankelevitz, Andrea D Branch, Rowena Yip, Sion K Roy, Sabee Molloi, Michael V McConnell, Ioannis Kakadiaris, George Abela, Nathan D. Wong

“…We previously reported new artificial intelligence (AI) algorithms applied to CAC scans for opportunistic measurement of bone mineral density, cardiac chamber volumes, left ventricular mass, and other imaging biomarkers collectively referred to as AI-cardiovascular disease (CVD). …”
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AUTOMATED BIM ENTITY RECONSTRUCTION FROM UNSTRUCTURED 3D POINTCLOUDS by Jan Voříšek, Bořek Patzák, Edita Dvořáková, Daniel Rypl

“…It provides a set of algorithms for automated or user assisted detection of fundamental entities from scanned point cloud data sets, such as floors, rooms, walls, and openings, and identification of the mutual relationships between them. …”
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Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems by Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

“…Addressing the growing challenges of vehicle density and traffic complexity, the system employs state-of-the-art deep learning techniques for real-time vehicle detection, tracking, and route analysis. Utilizing algorithms like YOLO for object detection, the system ensures an accurate and efficient monitoring across multiple surveillance nodes. …”
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Enhanced engine misfire diagnosis through integration of vibration and acoustic emission signals using artificial neural networks by Mohamed H. Abdelati, M. Mourad, Al-Hussein Matar, M. Rabie

“…Abstract An accurate Engine Misfire Detection diagnosis ensures the engine runs well and reduces emissions. …”
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An Efficient Deep Learning-Based Framework for Predicting Cyber Violence in Social Networks by Younes Fayand Fathabad, Mohammad Ali Balafar, Amin Golzari Oskouei, Kamal Koohi

“…However, this has also increased the prevalence of cyber violence, necessitating the development of automated detection methods. Deep learning-based algorithms have proven effective in identifying violent content, yet existing models often struggle with understanding contextual nuances and implicit forms of cyber violence. …”
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LSAP: A Learned Structure-Aware Pruning Point Cloud Classification Approach for Cyber Physical Social Intelligence by Xinhong Liu, Yangfan Li, Fengxiao Tang, Ming Zhao

“…To enhance the ability of Cyber Physical Social Intelligence (CPSI) to process three-dimensional spatial information, we investigate the problem of object detection in 3D Light laser Detection And Ranging (LiDAR) point clouds. …”
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The Necessity of CT Hip Scans in the Investigation of Occult Hip Fractures and Their Effect on Patient Management by Thomas Gatt, Daniel Cutajar, Lara Borg, Ryan Giordmaina

“…The frequency at which CT scan detects and alters management in occult hip fractures confirms the justification for its use. …”
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AGU2-Net: Multi-Scale U²-Net Enhanced by Attention Gate Mechanism for Image Tampering Localization by Kefei Wu, Lin Li, Qingyan Li

“…Although deep learning algorithms based on convolutional neural networks (CNNs) have made notable progress in image forgery detection, they still face certain limitations in effectively detecting and localizing tampered areas due to the subtle nature of existing manipulation traces. …”
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Research on Security Enhancement for Abnormal Content Release in Unified Audio Video Information service Systems by FENG Junhao

“…The system efficiently detects prohibited content while ensuring that legitimate content remains unaffected. …”
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ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. …”
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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…Abstract Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. …”
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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. …”
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Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Our results demonstrate that Cell-TRACTR exhibits strong performance in tracking and division accuracy compared to state-of-the-art algorithms, while also meeting traditional benchmarks in detection accuracy. …”
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A Data-Driven Machine Vision Framework for Quality Management in Photovoltaic Module Manufacturing by In-Bae Lee, Youngjin Kim, Sojung Kim

“…This experiment shows that the proposed framework enables the detection of PV module defects in electroluminescence (EL) and tabbing operations with a fault detection accuracy of over 95%. …”
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Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges by Mazhar Ali, Moharana Suchismita, Syed Saqib Ali, Bong Jun Choi

“…Recent studies have provided valuable insights into the potential of machine learning algorithms in SGs, covering areas such as generation, distribution, microgrids, consumer energy market, and cyber security. …”
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