Task-Oriented Adversarial Attacks for Aspect-Based Sentiment Analysis Models by Monserrat Vázquez-Hernández, Ignacio Algredo-Badillo, Luis Villaseñor-Pineda, Mariana Lobato-Báez, Juan Carlos Lopez-Pimentel, Luis Alberto Morales-Rosales

“…To conduct this evaluation, we propose diverse adversarial attacks across different dataset domains, target architectures, and consider distinct levels of victim model knowledge, thus obtaining a comprehensive evaluation. …”
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DeepGlioSeg: advanced glioma MRI data segmentation with integrated local-global representation architecture by Ruipeng Li, Yuehui Liao, Yueqi Huang, Xiaofei Ma, Guohua Zhao, Yanbin Wang, Chen Song

“…Test-time augmentation (TTA) and volume-constrained (VC) post-processing are subsequently applied to refine the final segmentation outputs.ResultsExtensive experiments were conducted on three publicly available glioma MRI datasets and one privately owned clinical dataset. …”
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PHYSICS-DRIVEN FEATURE CREATION TO IMPROVE MACHINE LEARNING MODELS PERFORMANCE FOR OIL PRODUCTION RATE PREDICTION by Eghbal Motaei, Seyed Mehdi Tabatabai, Tarek Ganat, Ahmad Khanifar, Sulaiman Dzaiy, Timur Chis

“…The study focuses on oil production prediction using a dataset that includes reservoir permeability, wellbore skin, reservoir pressure, net pay thickness, water cut, and well-liquid production rate. …”
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Ensemble-based customer churn prediction in banking: a voting classifier approach for improved client retention using demographic and behavioral data by Ruchika Bhuria, Sheifali Gupta, Upinder Kaur, Salil Bharany, Ateeq Ur Rehman, Seada Hussen, Ghanshyam G. Tejani, Pradeep Jangir

“…Using a comprehensive dataset including demographic, financial, and behavioral data—such as credit score, account balance, tenure, and activity levels—the study employs the goal variable revealing if a customer has left the bank. …”
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Reduction of monoclonal antibody viscosity using interpretable machine learning by Emily K. Makowski, Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock, Patrick Underhill, Emma Pelegri-O’Day, Erick Maglalang, Dwight Winters, Peter M. Tessier

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Neuromodulation of Attentional Control in Major Depression: A Pilot DeepTMS Study by Jodie Naim-Feil, John L. Bradshaw, Dianne M. Sheppard, Oded Rosenberg, Yechiel Levkovitz, Pinhas Dannon, Paul B. Fitzgerald, Moshe Isserles, Abraham Zangen

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An assessment of South African policy and strategic framework for the development of a sufficient, equitably distributed and well-performing health workforce for the implementation... by S V Mokoena, P Naidoo

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Computational analysis of congenital heart disease associated SNPs: unveiling their impact on the gene regulatory system by Shikha Vashisht, Costantino Parisi, Cecilia L. Winata

“…Initially, we curated a thorough dataset of SNPs from GWAS-catalog and ClinVar database and filtered them based on CHD-related traits. …”
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The clinical value and most informative threshold of polygenic risk score in the Quebec City Case-Control Asthma Cohort by Martin Pariès, Stéphanie Bougeard, Aida Eslami, Zhonglin Li, Michel Laviolette, Louis-Philippe Boulet, Evelyne Vigneau, Yohan Bossé

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Toward an Efficient Differentiation of Two <i>Diaporthe</i> Strains Through Mass Spectrometry for Fungal Biotyping by Kathleen Hernández-Torres, Daniel Torres-Mendoza, Gesabel Navarro-Velasco, Luis Cubilla-Rios

“…In addition, this is the first report of secondary metabolites in <i>D. melongenae</i>. The dataset demonstrates that the two strains under investigation can be distinguished via mass spectrometry, suggesting host affinity; both exhibits pronounced differences in their chemical profiles across all culture media and incubation periods with the parameters described herein.…”
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The Role of Prolactin as a Disease Activity Indicator in Some Rheumatic Diseases by Mohamed Ismail Abdelkarem, HM Fayed, Wael Abd El-Mohsen Abady, Eman Abulhagag Mohammed Mahmoud

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Enhanced detection of mild cognitive impairment in Alzheimer’s disease: a hybrid model integrating dual biomarkers and advanced machine learning by John Sahaya Rani Alex, R. Roshini, G. Maneesha, Jeetashree Aparajeeta, B. Priyadarshini, Chih-Yang Lin, Chi-Wen Lung

“…The experimental work presented in this study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The proposed hybrid model achieved an average accuracy of 93.6% for distinguishing between NC and symptomatic AD and 93.7% for discriminating between MCI and AD. …”
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Long-term memory plasticity in a decade-long connectivity study post anterior temporal lobe resection by Marine N. Fleury, Lawrence P. Binding, Peter Taylor, Fenglai Xiao, Davide Giampiccolo, Sarah Buck, Gavin P. Winston, Pamela J. Thompson, Sallie Baxendale, Andrew W. McEvoy, Matthias J. Koepp, John S. Duncan, Meneka K. Sidhu

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WED-YOLO: A Detection Model for Safflower Under Complex Unstructured Environment by Zhenguo Zhang, Yunze Wang, Peng Xu, Ruimeng Shi, Zhenyu Xing, Junye Li

“…The model is trained and validated using a custom-built safflower dataset. The experimental results demonstrate that the improved model achieves Precision (<i>P</i>), Recall (<i>R</i>), mean Average Precision (<i>mAP</i>), and <i>F</i>₁ score values of 93.15%, 86.71%, 95.03%, and 89.64%, respectively. …”
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Deformation and movement characteristics of debris flow landslide: A case study of the Shaziba landslide in Enshi, China by Zijian SHI, Wen CHEN, Yifan SHENG, Guangli XU

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Organ Donation Conversations on X and Development of the OrgReach Social Media Marketing Strategy: Social Network Analysis by Wasim Ahmed, Mariann Hardey, Josep Vidal-Alaball

“…The study was able to retrieve a dataset with 20,124 unique users and 33,830 posts. …”
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A Deep Learning Approach to Classify Fabry Cardiomyopathy from Hypertrophic Cardiomyopathy Using Cine Imaging on Cardiac Magnetic Resonance by Wei-Wen Chen, Ling Kuo, Yi-Xun Lin, Wen-Chung Yu, Chien-Chao Tseng, Yenn-Jiang Lin, Ching-Chun Huang, Shih-Lin Chang, Jacky Chung-Hao Wu, Chun-Ku Chen, Ching-Yao Weng, Siwa Chan, Wei-Wen Lin, Yu-Cheng Hsieh, Ming-Chih Lin, Yun-Ching Fu, Tsung Chen, Shih-Ann Chen, Henry Horng-Shing Lu

“…The model achieved impressive performance, with an F1-score of 0.846, an accuracy of 0.909, and an AUC of 0.914 when tested on the Taipei Veterans General Hospital (TVGH) dataset. Additionally, a single-blinding study and external testing using data from the Taichung Veterans General Hospital (TCVGH) demonstrated the reliability and effectiveness of the model, achieving an F1-score of 0.727, an accuracy of 0.806, and an AUC of 0.918, demonstrating the model’s reliability and usefulness. …”
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Multiscale Feature-Enhanced Water Body Detector of Truncated Gaussian Clutter in SAR Imagery by Bo Zhu, Yuli Xia, Yongsheng Zhou, Xiaoning Lv, Minqin Liu

“…The results are validated on the HISEA flooding dataset.…”
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Prenatal depression level prediction using ensemble based deep learning model by Abinaya Gopalakrishnan, Xujuan Zhou, Revathi Venkataraman, Raj Gururajan, Ka Ching Chan, Guohun Zhu, Niall Higgins

“…The accuracy of this approach applied to three benchmark datasets produced better results compared to all commonly applied machine learning models, including an Ensemble based Deep Learning model. …”
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Using a Two-Steps Clustering and PCA Analysis for Stratified Chronic Non-Cancer Pain Care: A Retrospective Cross-Sectional Study by Peiró AM, Barrachina J, Escorial M, Aguado I, Margarit C, Grimby-Ekman A

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