Advanced deep learning models based on neutrosophic logic for the analysis of brain tumor medical images by Dina Atef, Doaa El Shaha

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DRAMMA: a multifaceted machine learning approach for novel antimicrobial resistance gene detection in metagenomic data by Ella Rannon, Sagi Shaashua, David Burstein

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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…Existing studies introduced methods to detect code-level data leakage using manual and code analysis approaches. …”
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Fleet‐Wide Data‐Driven Model Generation Process for Residual‐Based Fault Detection in Wind Energy by Théodore Raymond, Sylvie Charbonnier, Christophe Bérenguer, Alexis Lebranchu

“…In this paper, a data‐driven automatic model generation method for fault detection, applicable to an entire fleet of wind turbines, is presented. …”
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Interpretable Machine Learning Biosignature Detection From Ocean Worlds Analogue CO2 Isotopologue Data by Lily A. Clough, Victoria DaPoian, Jonathan D. Major, Lauren M. Seyler, Brett A. McKinney, Bethany P. Theiling

“…We develop and test a new biosignature detection ML model using a novel, laboratory‐generated, CO2 isotopologue data set of analogue OW samples. …”
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Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data by Arkadiusz Syta, Arkadiusz Podkowiński, Tomasz Chorągiewicz, Robert Karpiński, Jakub Gęca, Dominika Wróbel-Dudzińska, Katarzyna E Jonak, Dariusz Głuchowski, Marcin Maciejewski, Robert Rejdak, Kamil Jonak

“…The Random Forest algorithm demonstrated the highest reliability, achieving an accuracy of 98% during training and 96% on the test set, while also identifying the most diagnostically relevant measurements. …”
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Training a convolutional neural network for exoplanet classification with transit photometry data by Juliana Wang

“…This paper applies a convolutional neural network (CNN) to the Kepler dataset, which consists of time-series light curve data from the Kepler Space Telescope, used for detecting exoplanets through transit events. …”
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Anomaly Detection in Spatiotemporal Data from Fiber Optic Distributed Temperature Sensing for Outdoor Fire Monitoring by Haitao Bian, Xiaohan Luo, Zhichao Zhu, Xiaowei Zang, Yu Tian

“…Results showed that, compared to AE and VAE models handling spatial or temporal data, the CNN-AE demonstrated superior anomaly detection performance and strong robustness when applied to spatiotemporal data. …”
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Enhanced Connectivity Validity Measure Based on Outlier Detection for Multi-Objective Metaheuristic Data Clustering Algorithms by Hossam M. J. Mustafa, Masri Ayob

“…Hence, this paper proposes an enhanced connectivity measure based on the outlier detection approach for multi-objective data clustering problems. …”
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Data Fusion of Electronic Nose and Multispectral Imaging for Meat Spoilage Detection Using Machine Learning Techniques by Vassilis S. Kodogiannis, Abeer Alshejari

“…Multispectral imaging and electronic noses are valuable techniques for the rapid and non-destructive detection of meat spoilage. In order to take advantage of the complementary information provided by these two different sensing devices, a high-level data fusion strategy was explored. …”
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An Open-Source Deep Learning Framework for Scalable Urban Heat Island Detection Using Geospatial Data by M. Akintola, G. Neziri

“…The framework’s open architecture, combined with publicly released datasets and modular code, ensures adaptability for use in both data-rich and resource-limited settings. This research contributes a transparent, scalable, and participatory approach to UHI detection, offering actionable insights for climate adaptation, heat risk mitigation, and sustainable urban planning. …”
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Detecting acute bilirubin encephalopathy in neonates based on multimodal MRI images and non-image clinical data by Miao Wu, Qian Liu, Can Lai

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Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

“…Additionally, including sampling time in the data sets significantly improves the model's predictive performance. …”
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Quantitative Detection Method for Surface Angled Cracks Based on Laser Ultrasonic Full-Field Scanning Data by Chenwei Wang, Rui Han, Yihui Zhang, Yuzhong Wang, Yanyang Zi, Jiyuan Zhao

“…Surface angled cracks on critical components in high-speed machinery can lead to fractures under stress and pressure, posing a significant threat to the operational safety of equipment. To detect surface angled cracks on critical components, this paper proposes a “Quantitative Detection Method for Surface Angled Cracks Based on Full-field Scanning Data”. …”
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A Methodological and Structural Review of Parkinson’s Disease Detection Across Diverse Data Modalities by Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…Monitoring this condition in real-world settings is crucial for detecting and managing adequate break periods. …”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…There is no universal method for detecting and/or eliminating outliers in data analysis theory. …”
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Topology for gaze analyses - Raw data segmentation by Oliver Hein, Wolfgang H. Zangemeister

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User and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study by Owain Tudor Jones, Natalia Calanzani, Suzanne E Scott, Rubeta N Matin, Jon Emery, Fiona M Walter

“… BackgroundSkin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. …”
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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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