Profiling antivaccination channels in Telegram: early efforts in detecting misinformation by Aelita Skarzauskiene, Monika Maciuliene, Aiste Dirzyte, Gintare Guleviciute

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Computed tomography-based conventional imaging features and texture analysis characteristics of chemotherapy drug-related acute pancreatitis by Quanlin Li, Chuanmei Liu, Zijian Fan, Hong Zhang, Zhiguo Kai

“…Imaging texture analysis may serve as a potential biomarker for its detection. …”
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Machine learning combined multi-omics analysis to explore key oxidative stress features in systemic lupus erythematosus by Hongwei Zhou, Xiaoqing Li, Yanyu Zhang, Feng Wei, Zhiyu Liu, Yan Zhao, Xubo Zhuang, Xia Liu, Haizhou Zhou

“…This study explores critical oxidative stress (OS) features and their interrelationships in SLE pathogenesis.MethodsThree transcriptomic datasets from the Gene Expression Omnibus (GEO) were analyzed to identify SLE- and OS-associated pathways via Gene Set Variation Analysis (GSVA). …”
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Transformer-Based Vulnerability Detection in IoT Firmware Binaries Using Opcode Sequences by M. Nandish, Jalesh Kumar, H. G. Mohan, M. V. Manoj Kumar

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Features of Creativity and Conceptual Thinking of Students Studying in the Direction of "Software Engineering "(Engineers-Kognitologs) by Ivakhnenko O.N., Smolyaninova V.A.

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Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective by Parisa Shahnazari, Kaveh Kavousi, Zarrin Minuchehr, Bahram Goliaei, Reza M Salek

“…Abstract In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. …”
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Complete mitochondrial genome of Houttuynia cordata sheds light on the evolution of complex structural features in early angiosperms by Yahui Huang, Bingyue Zhu, Siqi Hu, Wenbo Shi, Yuxue Liu, Qianhui Lin, Shuo Wang, Jing Yang, Chao Shi

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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fathima Fajila, Yuhanis Yusof

“…Apart from that, the proposed algorithm would also contribute to cancer-related issues upon verifying the relevancy of particular genes via technical analysis from a medical perspective and would be utilised in feature selection applications. …”
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Parafoveal OCT Angiography Features in Diabetic Patients without Clinical Diabetic Retinopathy: A Qualitative and Quantitative Analysis by Mathilde M. Goudot, Anne Sikorav, Oudy Semoun, Alexandra Miere, Camille Jung, Blandine Courbebaisse, Mayer Srour, Joseph G. Freiha, Eric H. Souied

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Beyond the nuclear border: single-cell analysis of in situ sequenced human brain tissue using cellular features by Janssen M. Kotah, Thomas Rust, Hilmar R. J. van Weering, Janneke Bosma, Amber L. Woudstra, Susanne M. Kooistra, Bart J. L. Eggen

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Orthostatic hypotension in Parkinson’s disease: effects on clinical features and disease severity-a systematic review and meta-analysis by Hui Wang, Chi Zhang, Dongxun Xu

“…Meta-regression was conducted to detect the potential influences of disease duration on the differences in clinical features between PD patients with and without OH.ResultsA total of 26 articles involving 3,992 patients with Parkinson’s disease were included in our study. …”
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Adaptive convolutional neural network-based principal component analysis algorithm for the detection of manufacturing data by Tsun-Kuo Lin

“…Herein, an adaptive convolutional neural network (CNN)-based principal component analysis (PCA) algorithm for the detection of manufacturing data is proposed. …”
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Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

“…Depression is a significant mental health problem and presents a challenge for the machine learning field in the detection of this illness. This study explores automated depression classification, leveraging computational techniques to address this issue. …”
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Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution by Norah A. Al-Johany, Fathy E. Eassa, Sanaa A. Sharaf, Eynas H. Balkhair, Sara M. Assiri

“…This paper presents a novel static analysis tool designed to detect and automatically correct concurrency-related defects in OpenMP programs. …”
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Automated Detection of Galactic Rings from Sloan Digital Sky Survey Images by Linn Abraham, Sheelu Abraham, Ajit K. Kembhavi, N. S. Philip, A. K. Aniyan, Sudhanshu Barway, Harish Kumar

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Machine Learning-Driven Radiomics Analysis for Distinguishing Mucinous and Non-Mucinous Pancreatic Cystic Lesions: A Multicentric Study by Neus Torra-Ferrer, Maria Montserrat Duh, Queralt Grau-Ortega, Daniel Cañadas-Gómez, Juan Moreno-Vedia, Meritxell Riera-Marín, Melanie Aliaga-Lavrijsen, Mateu Serra-Prat, Javier García López, Miguel Ángel González-Ballester, Maria Teresa Fernández-Planas, Júlia Rodríguez-Comas

“…Feature selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression, followed by classification with an Adaptive Boosting (AdaBoost) model trained on the optimized feature set. …”
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Ensemble Machine Learning Models Utilizing a Hybrid Recursive Feature Elimination (RFE) Technique for Detecting GPS Spoofing Attacks Against Unmanned Aerial Vehicles by Raghad Al-Syouf, Omar Y. Aljarrah, Raed Bani-Hani, Abdallah Alma’aitah

“…Therefore, this paper proposes a hybrid Recursive Feature Elimination (RFE) technique based on feature importance ranking along with a Spearman Correlation Analysis (SCA). …”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…However, they are not immune to security flaws, which can result in significant financial losses. These flaws can be detected using dynamic analysis methods that extract various aspects from smart contract bytecode. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

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Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI by Wang Xu, Xiangjiang Shi

“…This study proposes a hybrid framework combining radiomic texture analysis with deep learning-based segmentation to enhance MI detection on non-contrast cine cardiac magnetic resonance (CMR) imaging.The approach incorporates radiomic features derived from the Gray-Level Co-Occurrence Matrix (GLCM) and Gray-Level Run Length Matrix (GLRLM) methods into a modified U-Net segmentation network. …”
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