Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

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Atrial Tachyarrhythmias and Atrial Flutter: the Basics of Diagnostics and Modern Opportunities of Therapy by Yu. A. Bunin, S. A. Miklishanskaya, E. A. Zolozova, V. V. Chigineva

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CASSNet: Cross-Attention Enhanced Spectral–Spatial Interaction Network for Hyperspectral Image Super-Resolution by Zhanxu Zhang, Linzi Yang, Guanglian Zhang, Jiangwei Deng, Lifeng Bian, Chen Yang

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Locating and quantifying CH₄ sources within a wastewater treatment plant based on mobile measurements by J. Yang, Z. Xu, Z. Xia, Z. Xia, X. Pei, Y. Yang, B. Qiu, B. Qiu, S. Zhao, S. Zhao, Y. Zhang, Y. Zhang, Z. Wang, Z. Wang

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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD by Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah

“…Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. …”
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Susceptibility assessment of freeze-thaw erosion induced debris flow using random forest, Eastern Tibetan Plateau by Yongjie Yang, Yongjie Yang, Yongjie Yang, Yuqi Zhang, Yuqi Zhang, Yuqi Zhang, Hai Huang, Hai Huang, Jinsong Zhu, Jinsong Zhu, Jinsong Zhu, Qiwei Lv, Qiwei Lv, Qiwei Lv, Jiang Peng, Jiang Peng

“…Subsequently, the freeze-thaw erosion index, a new control factor gauging the intensity of freeze-thaw erosion in the study area, was incorporated, and the susceptibility assessment was also conducted using the Random Forest Algorithm (Freeze-thaw erosion model, FEM). The results show that FEM improved accuracy by 0.457 and AUC by 0.0541 compared to NFEM, indicating enhanced predictive performance. …”
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A Study on the Management and Evolution of Land Use and Land Cover in Romania During the Period 1990–2022 in the Context of Political and Environmental Changes by Jenica Călina, Aurel Călina, Gheorghe Marian Vangu, Alin Constantin Croitoru, Marius Miluț, Nicolae Ion Băbucă, Ion Stan

“…Land use and land cover are the main anthropogenic factors that lead to the rapid and aggressive degradation of land and interfere with the functioning of ecosystems, especially through the expansion of urbanization and the reduction in forested areas. The purpose of this article is to identify sources of official data and to build an updated dataset upon which analysis algorithms can be applied. …”
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Novel Spatio-Temporal Joint Learning-Based Intelligent Hollowing Detection in Dams for Low-Data Infrared Images by Lili Zhang, Zihan Jin, Yibo Wang, Ziyi Wang, Zeyu Duan, Taoran Qi, Rui Shi

“…Furthermore, it attained a sub-10% cross-sectional calculation error for hollowing dimensions, outperforming maximum entropy (70.5% error reduction) and OTSU (7.4% error reduction) methods, which shows our method being one novel method for automated intelligent hollowing detection.…”
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Mapping the ADDQoL to the EQ-5D-5L and SF-6Dv2 among Chinese patients with type 2 diabetes mellitus by Haoran Fang, Tianqi Hong, Xinran Liu, Chang Luo, Yuanyuan Hou, Shitong Xie

“…This study developed mapping algorithms to predict EQ-5D-5L and SF-6Dv2 utility values from ADDQoL scores in T2DM patients in China. …”
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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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Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping by Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero

“…We assessed the ability of these methods to predict bathymetries over successive years subsequent to algorithm calibration, as well as their capacity to estimate depths of other areas not included in model calibration, thereby evaluating temporal and spatial independence, respectively. …”
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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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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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Resolving the observe zone: validation of the ESC 0/3-hour and the APACE criteria for NSTEMI triage by Christian Müller, Norbert Frey, Moritz Biener, Evangelos Giannitsis, Pedro Lopez-Ayala, Christoph Reich, Mustafa Yildirim, Christian Salbach

“…For diagnosing NSTEMI, the ESC 0/3-hour criteria showed lower sensitivity (69.4%) than the criteria defined in the Advantageous Predictors of Acute Coronary Syndromes Evaluation (APACE) study (86.1%, p=0.053), with both having high negative predictive value (93.5% vs 87.5%, p=0.339). By definition, the ESC 0/3-hour algorithm categorises all patients into rule-in or rule-out, eliminating the need for an OZ, whereas 55.6% of patients remained in the OZ with the APACE criteria. …”
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Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…By enabling objective and reproducible analysis of OCT biomarkers, deep learning algorithms provide critical insights into treatment response. …”
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Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study by Yanli Guo, Hongxia Zhang, Yang Guang, Wen He, Bin Ning, Chen Yin, Mingchang Zhao, Fang Nie, Pintong Huang, Rui-Fang Zhang, Qiang Yong, Jianjun Yuan, Yicheng Wang, Lijun Yuan, Litao Ruan, Tengfei Yu, Haiman Song, Yukang Zhang

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