Credit Rating Model Based on Improved TabNet by Shijie Wang, Xueyong Zhang

“…Under the rapid evolution of financial technology, traditional credit risk management paradigms relying on expert experience and singular algorithmic architectures have proven inadequate in addressing complex decision-making demands arising from dynamically correlated multidimensional risk factors and heterogeneous data fusion. …”
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Equivariant learning leveraging geometric invariances in 3D molecular conformers for accurate prediction of quantum chemical properties by Jianhua Sun, Ye Cao, Huijing Hu, Baoqiao Qi

“…The foundation of the 3DMSE approach lies in an equivariant learning module that adeptly captures the subtle geometric intricacies of molecular conformers while ensuring invariance to rotations and permutations. …”
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Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Algorithmic recommendation mechanisms of social media platforms, viral diffusion of user-generated content (UGC), and real-time public opinion pressures are fundamentally deconstructing the traditional corporate crisis response paradigm that used to rely on one-way statements and delayed reactions. …”
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Usage of short video applications (SVAs): Exploring Italian users’ social representations of short video creators and trust in informational and educational SVA content providers by Willow-G. Curry, Elisa Colì

“…Informational and sports & entertainment are the primary types of content viewed across all age groups. While younger users place greater emphasis on professional skills and authoritative content, older users tend to prioritize engagement and presentation skills. …”
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Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation by A. Srinivaas, N. R. Sakthivel, Binoy B. Nair

“…The former uses physical models of engine components to diagnose defects, while the latter employs statistical analysis of sensor data to identify patterns indicating faults. …”
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Research on the robustness of the open-world test-time training model by Shu Pi, Xin Wang, Jiatian Pi

“…However, deploying TTT/TTA in open-world environments is challenging due to the difficulty in distinguishing between strong out-of-distribution (OOD) samples and regular weak OOD samples. While emerging Open-World TTT (OWTTT) approaches address this challenge, they introduce a new vulnerability: test-time poisoning attacks. …”
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Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation by Marco Negozio, Lorenzo Donati, Adrian H. A. Lutey

“…PCG formation was predicted with 5.8% false negatives and 3.9% false positives compared to 10.1% and 18.1%, respectively, with existing analytical models, while grain size was predicted with a mean squared error (MSE) of 9.77 μm2 compared to 48.3 μm2. …”
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Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices by Alexis Courbet, Patrick Amar, François Fages, Eric Renard, Franck Molina

“…We show that proof‐of‐concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. …”
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Twofold dynamic attention guided deep network and noise-aware mechanism for image denoising by Zihao Chen, Alex Noel Joseph Raj, Vijayarajan Rajangam, Wei Li, Vijayalakshmi G.V. Mahesh, Zhemin Zhuang

“…While employing deeper networks, network performance improves with the cost of additional computational requirements. …”
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Artificial Intelligence‐Based Approaches for AAV Vector Engineering by Fangzhi Tan, Yue Dong, Jieyu Qi, Wenwu Yu, Renjie Chai

“…This review compares traditional and AI‐based methods of AAV vector engineering and highlights recent research in AAV engineering using AI algorithms.…”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…This study addresses the critical challenge of optimizing drone flight parameters for enhanced object detection in video streams. While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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Hardware Evaluation of Interference Alignment Techniques Under Different Channel State Information Updating Rates by David Alejandro Urquiza Villalonga, Alejandro Lopez Barrios, Maximo Morales-Cespedes, M. Julia Fernandez-Getino Garcia

“…In this context, interference alignment (IA) algorithms have been proposed to manage interference while increasing the achievable degrees of freedom. …”
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Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

“…Pre-processing in both algorithms focuses on segmentation of heart sounds into discrete cardiac cycles. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. …”
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Construction of a stromal cell-related prognostic signature based on a 101-combination machine learning framework for predicting prognosis and immunotherapy response in triple-nega... by Fanrong Li, Congnan Jin, Yacheng Pan, Zheng Zhang, Liying Wang, Jieqiong Deng, Yifeng Zhou, Yifeng Zhou, Binbin Guo, Shenghua Zhang, Shenghua Zhang

“…A consensus MVP cell-related signature (MVPRS) was developed using 10 machine learning algorithms and 101 model combinations and validated in training and validation cohorts. …”
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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. …”
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Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

“…CIBERSORT was applied to assess immune cell infiltration, while spatial transcriptomics mapped the regional expression of key genes. …”
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Klasifikasi Katarak Berdasarkan Optic Disc Citra Fundus Smartphone: Perbandingan Ekstraksi Ciri Tekstur Dan Metode Neural Network by Muchtar Ali Setyo Yudono, Fabrobi Fazlur Ridha, Dani Mardiyana, Faturrohman Al-Ghozi, Aldi Maulana

“…Conventional fundus cameras, while effective, are expensive and less portable, limiting accessibility in remote areas. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…In the past decade, with the continuous progress of artificial intelligence, algorithms based on deep learning have become one of the main methods for cloud detection. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…The results of non-linear regression show that actual noise has an inhibitory effect on cognitive enhancement and stress relief, while moderate perceived noise can promote emotional restoration and stress relief. …”
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