Distribution and sources of fallout ¹³⁷Cs and ^239+240Pu in equatorial and Southern Hemisphere reference soils by G. Dicen, G. Dicen, F. Guillevic, S. Gupta, P.-A. Chaboche, P.-A. Chaboche, P.-A. Chaboche, K. Meusburger, P. Sabatier, O. Evrard, C. Alewell

“…Our machine learning algorithm identified the precipitation of the coldest quarter, longitude, and latitude as the strongest predictors of the <span class="inline-formula">¹³⁷</span>Cs inventory. …”
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Object-Specific Multiview Classification Through View-Compatible Feature Fusion by Javier Perez Soler, Jose-Luis Guardiola, Nicolás García Sastre, Pau Garrigues Carbó, Miguel Sanchis Hernández, Juan-Carlos Perez-Cortes

“…In these scenarios, relying on a single image may not provide sufficient information to effectively identify the scrutinized object, as different perspectives may reveal distinct characteristics that are essential for accurate classification. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…Data processing algorithms were introduced to process the source data, fuse their features, and augment the datasets. …”
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A FixMatch Framework for Alzheimer&#x2019;s Disease Classification: Exploring the Trade-Off Between Supervision and Performance by Al Hossain, Umme Hani Konok, MD Tahsin, Raihan Ul Islam, Mohammad Rifat Ahmmad Rashid, Mohammad Shahadat Hossain, Karl Andersson

“…In this work, we explore whether the FixMatch algorithm&#x2014;a semi-supervised learning approach&#x2014;can aid in classifying Alzheimer&#x2019;s Disease (AD), Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) by using the ADNI fMRI dataset of 5,182 images. …”
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Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy by Ze-Ning Huang, Hao-Xiang Zhang, Yu-Qin Sun, Xing-Qi Zhang, Yi-Fen Lin, Cai-Ming Weng, Chao-Hui Zheng, Ping-Li, Jia-Bin Wang, Qi-Yue Chen, Long-Long Cao, Mi Lin, Ru-Hong Tu, Chang-Ming Huang, Jian-Xian Lin, Jian-Wei Xie

“…With its predictive capabilities, this tool shows promise for enhancing clinical decision-making processes in the future. Methods This study utilized a multicenter cohort design, retrospectively gathering clinical data and computed tomography (CT) images from 268 patients diagnosed with advanced gastric cancer who underwent neoadjuvant immunotherapy between January 2019 and December 2023 from two medical centers. …”
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Application of Deep Learning Techniques in Uranium Microparticle Fission Track Detection by ZHAO Xiong, REN Fangda, SHEN Yan

“…After cooling, the samples were transferred to a microscope to obtain the original images of uranium microparticle fission tracks. The YOLOv5 algorithm, a deep learning approach, was employed as the foundational network model. …”
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Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…The approach was developed using three large-scale spectral datasets (n = 911), including soil RGB images acquired by a smartphone, laboratory visible and near-infrared spectra using diffuse reflectance spectroscopy (DRS), and remotely sensed bare soil spectra (RSBS) from Sentinel-2 imagery, and further validated against three independent datasets of the same types (n = 72) at catchment scale. …”
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Quantum metamaterials: Applications in quantum information science by Solomon Uriri, Yaseera Ismail, Mhlambululi Mafu

“…We restrict this study to quantum state manipulation and control, quantum entanglement, single photon generation, quantum state switching, quantum state engineering, quantum key distribution, quantum algorithms, orbital angular momentum, and quantum imaging. …”
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Spectrogram-Based Arrhythmia Classification Using Three-Channel Deep Learning Model with Feature Fusion by Alaa Eleyan, Fatih Bayram, Gülden Eleyan

“…The proposed methodology transforms the ECG time series into a spectrogram image using a short-time Fourier transform (STFT). …”
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A simple method to back-project isocenter dose of radiotherapy treatments using EPID transit dosimetry by Thiago Bernardino da Silveira, Bianca de Quadros Cerbaro, Luiz Antônio Ribeiro da Rosa

“…The aim of this work was to implement a simple algorithm to evaluate isocenter dose in a phantom using the back-projected transmitted dose acquired using an Electronic Portal Imaging Device (EPID) available in a Varian Trilogy accelerator with two nominal 6 and 10 MV photon beams. …”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The extracted features were then processed by a set of ML algorithms along with a voting ensemble approach. …”
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Synergizing remote sensing, support vector machine, and aeromagnetic data for precise lithological and mineral potential mapping: a case study from Egypt by Hatem M. El-Desoky, Ahmed M. Abdel-Rahman, Hamada El-Awny, Wael Fahmy, Reda Abdu Yousef El-Qassas, Kamal Abdelrahman, Hassan Alzahrani, Peter Andráš, Yahia Z. Amer, Ahmed M. Eldosouky

“…Therefore, we effectively mapped the exposed rock units in the Hamash region of the Eastern Desert of Egypt by using Support Vector Machine (SVM) to Sentinel 2 data through executing machine learning algorithms (MLAs). This goal involves extensive fieldwork, petrographical examinations, and image processing remote sensing techniques to accurately reveal the exposed lithologies distribution besides the potential relic areas. …”
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The hermeneutic circle as a means of illustration of the understanding problem when teaching didactic communications by E. E. Neupokoeva, N. K. Chapaev

“…The publication considers the hermeneutic circle model as a visual image that illustrates the specifics of cognitive processes when studying user algorithms as the basis for information exchange in the field of IT. …”
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Retinal revelations: Seeing beyond the eye with artificial intelligence by John Davis Akkara

“…This field, known as oculomics, leverages AI and deep learning algorithms to process vast amounts of data from imaging techniques such as fundus photography, optical coherence tomography (OCT), OCT angiography, infrared iris imaging, slit-lamp photography, and external eye photography. …”
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Artificial intelligence for diagnosing rare bone diseases: a global survey of healthcare professionals by Behnam Javanmardi, Rebekah L. Waikel, Tinatin Tkemaladze, Shahida Moosa, Alexander Küsshauer, Jean Tori Pantel, Minu Fardipour, Peter Krawitz, Benjamin D. Solomon, Klaus Mohnike

“…Establishing correlations between genotype and phenotype (mainly via imaging) is critical for diagnosing RBDs. Image recognition artificial intelligence (AI) has the potential to significantly improve the diagnostic process by assisting healthcare providers to identify and differentiate imaging patterns associated with various RBDs. …”
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Predicting brain age for veterans with traumatic brain injuries and healthy controls: an exploratory analysis by John P. Coetzee, John P. Coetzee, Xiaojian Kang, Xiaojian Kang, Victoria Liou-Johnson, Victoria Liou-Johnson, Victoria Liou-Johnson, Ines Luttenbacher, Srija Seenivasan, Elika Eshghi, Daya Grewal, Siddhi Shah, Frank Hillary, Emily L. Dennis, Emily L. Dennis, Maheen M. Adamson, Maheen M. Adamson, Maheen M. Adamson

“…High-resolution T1W images were processed using FreeSurfer 7.0. pBAs were calculated from T1s. …”
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Developing an Uncrewed Aerial Vehicle (UAV)-Based Prediction Model for the Rice Harvest Index Using Machine Learning by Zhaoyang Pan, Zhanhua Lu, Liting Zhang, Wei Liu, Xiaofei Wang, Shiguang Wang, Hao Chen, Haoxiang Wu, Weicheng Xu, Youqiang Fu, Xiuying He

“…UAV obtained visible light and multispectral images of different varieties, and the data such as digital surface elevation, visible light reflectance, and multispectral reflectance were extracted after processing for correlation analysis. …”
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Improved soil moisture retrieval during crop growing season using passive microwave data at L-band by Minfeng Xing, Kai Cui, Taifeng Dong, Ming Ma, Xin Zhou, Yi Zhang

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New method for landslide susceptibility evaluation in alpine valley regions that considers the suitability of InSAR monitoring and introduces deformation rate grading by Dingyi Zhou, Zhifang Zhao, Wenfei Xi, Xin Zhao, Jiangqin Chao

“…Incorporating Interferometric Synthetic Aperture Radar (InSAR) data sources into the landslide susceptibility evaluation process has yielded favorable outcomes in some studies. …”
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The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets by Theresa Willem, Alessandro Wollek, Theodor Cheslerean-Boghiu, Martha Kenney, Alena Buyx

“…As a standard, categorical data, such as patients’ gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population. …”
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