Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…Further it is found that the mean‐squared difference between predictions of the model and observed values of the velocity are substantially lower than the same quantity calculated for an existing climatology that was not formed with ML techniques.…”
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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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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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Control system design for azimuth position of earth station antennas by Auday Al-Mayyahi, Ammar Aldair, Zainab A. Khalaf, William Wang

“…The camel optimization algorithm (COA) was used to obtain the optimal design parameters of each controller in the considered scenarios.…”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…A dataset of 101,710 frames was selected based on specific algorithmic rules from synchronized StatsBomb event data and tracking data of 580 Premier League matches. …”
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Artificial Intelligence for Financial Accountability and Governance in the Public Sector: Strategic Opportunities and Challenges by Ceray Aldemir, Tuğba Uçma Uysal

“…However, challenges such as algorithmic bias, data privacy issues, and the need for strong ethical guidelines still exist, and these could hinder the equitable use of AI. …”
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Transductive zero-shot learning via knowledge graph and graph convolutional networks by Qiong Li, Xin Sun, Junyu Dong

“…During testing, a clustering strategy, the Double Filter Module with Hungarian algorithm, is applied to the unseen samples, and then, the learned classifiers are used to predict their categories. …”
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FRESH: Fusion-Based 3D Apple Recognition via Estimating Stem Direction Heading by Geonhwa Son, Seunghyeon Lee, Yukyung Choi

“…Secondly, we designed a 3D detection algorithm that not only recognizes the dimensions and location of apples, as existing methods do, but also predicts their 3-axis rotation. …”
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Machine learning approach for studying the neural underpinnings of dyslexia on a phonological awareness task by Christoforos Christoforou, Timothy C. Papadopoulos, Maria Theodorou

“…Results showed that the proposed phoneme-related neural-congruency components are predictive about the underlying neuronal differences amongst groups. …”
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Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs by Thomas Hügle, Elisabeth Rosoux, Guillaume Fahrni, Deborah Markham, Tobias Manigold, Fabio Becce

“…CPPD presence was then predicted using a convolutional neural network. We tested seven CPPD models, each with a different combination of sites out of TFCC, MCP-2 and MCP-3. …”
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Evaluating the utility of public-facing jail registers to inform public health practice, Washington state 2023 by Steven Erly, Richard J. Lechtenberg, Vasiliki Georgoulas-Sherry, Anna Berzkalns, Allison Moore, Julia C. Dombrowski, Jennifer E. Balkus

“…We compared the sensitivity and positive predictive value (PPV) of the algorithm applied to the reduced datasets and calculated an estimate for the entire dataset weighted by incarcerated population size. …”
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Utilizing Multi-omics analysis to elucidate the role of mitochondrial gene defects in Gastric cancer progression. by Jie Chu, Hanying Song, Kemin Fu, Wei Xiao, Jiudong Jiang, Qixin Gan, Bo Deng

“…Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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Foreign object detection for mining conveyor belts based on YOLOv5n-CND by SUN Aoran, ZHAO Peipei, YANG Di, ZHANG Junyi, YU Hongjian

“…To address the issues of complex background in foreign object images, weak feature extraction, low detection accuracy for adhering small objects, and distortion in detection box positioning and scale, a foreign object detection algorithm for mining conveyor belts based on YOLOv5n-CND is proposed. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Gene expression in single cell RNA sequencing (scRNA-seq) data was assessed using the AUcell algorithm. In the TCGA [LUAD] dataset, disulfidptosis-related enrichment scores were calculated using ssGSEA, and core gene sets were identified through the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. …”
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GPR65 is a novel immune biomarker and regulates the immune microenvironment in lung adenocarcinoma by Hanxu Zhou, Zhi Chen, Shuang Gao, Chaoqun Lian, Junjie Hu, Jin Lu, Lei Zhang

“…We screened differential genes (DEGs) in the immune and stromal components, and then screened modular genes by the WGCNA algorithm, which were intersected with DEGs and incorporated into the LASSO-COX regression model. …”
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Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population by Mendoza-Mendoza MM, Acosta-Jiménez S, Galván-Tejada CE, Maeda-Gutiérrez V, Celaya-Padilla JM, Galván-Tejada JI, Cruz M

“…By identifying sex-specific predictive features, this work supports the development of precision medicine tools tailored to the Mexican population. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…The LandTrendr (LT) algorithm was used in GEE to collect ground control points in no-change areas automatically. …”
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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

“…To identify a subset of distinct, minimally redundant, predictive variables, we used the statistically equivalent signature algorithm. …”
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Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study by Yao Wang, Jiarui Chen, Yueqiong Ni, Yan Liu, Xiang Gao, Michael Andrew Tse, Gianni Panagiotou, Aimin Xu

“…Furthermore, a machine-learning algorithm built using baseline microbial signatures and clinical characteristics predicted exercise responsiveness in improvements of insulin sensitivity, with an area under the receiver operating characteristic (AUROC) of 0.91 (95% CI: 0.85–0.97) in the discovery cohort and of 0.79 (95% CI: 0.74–0.86) in the independent validation cohort (n = 30).Conclusions Our findings suggest that intense exercise training significantly remodels the human fungal microbiome composition. …”
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Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study by Anneleen Dereymaeker, Vladimir Matic, Jan Vervisch, Perumpillichira J. Cherian, Amir H. Ansari, Ofelie De Wel, Paul Govaert, Maarten De Vos, Sabine Van Huffel, Gunnar Naulaers, Katrien Jansen

“…EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. …”
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