Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

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Development of wireless electronic nose and using of remote monitoring by HU Ying, WANG Jun

“…At the same time, selecting the appropriate pattern recognition algorithm can make the system more accurate.…”
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Development and evaluation of customized software to automatically align macula and optic disc centered scanning laser ophthalmoscope fundus images by M. Elena Martinez-Perez, Franziska G. Rauscher, Pingping Zhao, Tobias Elze

“…The optic disc-fovea angle markedly influences the regional distribution of retinal layer thickness patterns, specifically the retinal nerve fiber layer thickness measured at the optic disc. …”
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A scoping review and bibliometric analysis (ScoRBA) of machine learning in genetic data analysis: unveiling the transformative potential by Zakaria et al.

“…The important domains identified are Cancer Genomics, Bioinformatics, Precision Medicine, Disease Biomarkers, and Genetic Algorithms. These domains benefit from ML's data-driven insights, which have the potential to revolutionize healthcare and biomedical research. …”

A comprehensive review of flood damage in mountainous regions: challenges, solutions, and advanced management technologies by Mohammad Roohi, Jila Dehghani, Maryam Irani, Paramiss Mina

“…This work employs techniques such as LiDAR for precise topographic models, integrating remote sensing with hydrological/hydraulic models, and analyzing satellite imagery to study flood patterns and land cover changes. Furthermore, a precise and useful understanding of the effects of floods in these areas has been made possible by the use of machine learning algorithms to forecast flood episodes and evaluate damage, in conjunction with field research and community participation, such as citizen science initiatives for data collection and local knowledge integration. …”
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Bridging aging, immunity, and atherosclerosis: novel insights into senescence-related genes by Yan Lu, Rong Yuan, Rong Yuan, Qiqi Xin, Qiqi Xin, Keji Chen, Keji Chen, Weihong Cong, Weihong Cong

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Key Generation and Testing Based on Biometrics by Alaa AbdulRaheeM, shahd Abdulrhman Hasso

“…Creating and testing a biometric key is a critical process used for security and identity verification .When using biometric traits such as fingerprints, facial features, iris patterns, earprints, and voice patterns, a unique key is created and linked to the individual's biometric identity. …”
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Objective determination of initiation stress and damage stress in rock failure using acoustic emission and digital image correlation by Peng Liang, Yanbo Zhang, Xulong Yao, Guangyuan Yu, Qiang Han, Junling Liu

“…Three damage variables were established based on the cumulative counts of acoustic emission shear waves, primary waves, and principal strain, and their evolution patterns were analyzed. The research aimed to explore a method for determining rock characteristic stresses by integrating acoustic emission monitoring with the DIC method. …”
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Ultrasound Imaging and Machine Learning to Detect Missing Hand Motions for Individuals Receiving Targeted Muscle Reinnervation for Nerve-Pain Prevention by Anna Rita E. Moukarzel, Justin Fitzgerald, Marcus Battraw, Clifford Pereira, Andrew Li, Paul Marasco, Wilsaan M. Joiner, Jonathon Schofield

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Small-sample-data augmentation and transfer strategies for forest cover change monitoring by Kun Feng, Shaoxiu Ma, Haiyang Xi, Linhao Liang, Weiqi Liu, Atsushi Tsunekawa

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Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

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Prediction method of gas content in deep coal seams based on logging parameters: A case study of the Baijiahai region in the Junggar Basin by Yijie Wen, Shu Tao, Fan Yang, Yi Cui, Qinghe Jing, Jie Guo, Shida Chen, Bin Zhang, Jincheng Ye

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Access and benefit sharing biological materials for machines: Artificial intelligence, machine learning and deep learning by Charles Lawson, Elizabeth Englezos, Michelle Rourke

“…Societal Impact Statement Future research and development of biological materials for foods, feeds, fibres, materials and medicines will increasingly rely on information and knowledge using Artificial Intelligence (AI) applications for detecting patterns to make useful decisions. …”
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Backfire Effect Reveals Early Controversy in Online Media by Songtao Peng, Tao Jin, Kailun Zhu, Qi Xuan, Yong Min

“…Our work highlights a new psychological perspective on conflict behavior in online discussions and bridges behavioral patterns and computational modeling.…”
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A machine learning approach to identifying key predictors of Peruvian school principals' job satisfaction by Luis Alberto Holgado-Apaza, Dany Dorian Isuiza-Perez, Nelly Jacqueline Ulloa-Gallardo, Yban Vilchez-Navarro, Ruth Nataly Aragon-Navarrete, Wilian Quispe Layme, Marleny Quispe-Layme, Danger David Castellon-Apaza, Remo Choquejahua-Acero, Jaime Cesar Prieto-Luna

“…Despite the significance of this issue, there is limited research on satisfaction predictors for these professionals, particularly using machine learning approaches. …”
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GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis by Asier Ortega-Legarreta, Alberto Maillo, Daniel Mouzo, Ana Rosa López-Pérez, Lara Kular, Majid Pahlevan Kakhki, Maja Jagodic, Jesper Tegner, Vincenzo Lagani, Ewoud Ewing, David Gomez-Cabrero

“…Methodologically, GeneSetCluster 2.0 introduces a novel approach to address duplicated gene-sets and implements a seriation-based clustering algorithm that reorders results, aiding pattern identification. …”
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Investigating the Complexity of Multidimensional Symptom Experiences in Patients With Cancer: Systematic Review of the Network Analysis Approach by Vincent Richard, Allison Gilbert, Emanuela Pizzolla, Giovanni Briganti

“…Several NA approaches were used: network visualization (n=1), Bayesian network (n=1), pairwise Markov random field and IsingFit method (n=1), unregularized Gaussian graphical model (n=2), regularized partial correlation network (n=6), network visualization and community NA (n=1), network visualization and Walktrap algorithm (n=1), undirected network model with the Fruchterman-Reingold and edge-betweenness approaches (n=4), biased correlation and concise pattern diagram (n=1), extended Bayesian information criterion graphical LASSO method (n=3), cross-lagged panel network (n=1), and unspecified NA (n=3). …”
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Experimental Test Procedure of the Spatial Distribution of Environmental Parameters and Products of Combustion in a Residential Area and Adjacent Spaces by A. A. Antoshyn, S. A. Volkau

“…This article is dedicated to the issue of efficiency increase of fire detection equipment in living accommodation and adjacent spaces. This research is intended to develop the testing methodology for spatial pattern of combustion products, including toxic gases with asphyxiant and irritant effects, in both height and area of rooms in a standard apartment building, as well as correlation identification between controlled by fire alarm parameters of environment in living rooms and dangerous fire factors.Proposed methodology includes the concentration measurement of the basic gaseous combustion products (asphyxiant and irritant), generated in the process of materials burning in living accommodation. …”
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Restoring Authenticity: Literary, Linguistic, and Computational Study of the Manuscripts of Tchaikovsky’s <i>Children’s Album</i> by Evgeny Pyshkin, John Blake

“…These methods are supported by the technology provided by computational linguistics, such as large language models along with music analysis algorithms based on signature pattern elicitation. This article examines how artificial intelligence technologies can shed light on the differing views on the <i>Children’s Album.…”
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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure by Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

“…Research in spatial epidemiology relies on both conventional approaches and Machine- Learning (ML) algorithms to explore geographic patterns of diseases and identify influential factors (Pfeiffer & Stevens, 2015). …”
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