Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases by Ana Gutiérrez, Jose Aguilar, Ana Ortega, Edwin Montoya

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Identification and validation of glycosylation-related gene signatures for prognostic stratification in sepsis by Chunyang Li, Haiyan Xue, Haiyan Xue, Lihe Chen, Fengxue Zhu, Jie Li

“…Glycosylation is one of the key modes of protein modification, affecting protein folding, transportation, and localization. Glycosylation patterns are closely related to sepsis, but their specific impact still needs further investigation. …”
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Hybrid Android Malware Detection and Classification Using Deep Neural Networks by Muhammad Umar Rashid, Shahnawaz Qureshi, Abdullah Abid, Saad Said Alqahtany, Ali Alqazzaz, Mahmood ul Hassan, Mana Saleh Al Reshan, Asadullah Shaikh

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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

“…This enables the models to discern intricate data patterns and establish correlations between selected features and patient survival. …”
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Study of ESG transformation of the region by the artificial intelligence system by Nikolay I. Lomakin, Tatyana I. Kuzmina, Maxim S. Maramygin, Olga V. Yurova, Oksana A. Minaeva, Aleksey A. Polozhentsev, Tamila D. Eliseeva

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Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer by Xiao Guo, Chuanbo Feng, Jiaying Xing, Yuyan Cao, Tengda Liu, Wenchuang Yang, Runhong Mu, Tao Wang

“…Epigenetic changes play a critical role in breast cancer progression and therapy responses, providing a foundation for prognostic model development.MethodsWe developed the Machine Learning-derived Epigenetic Model (MLEM) to identify prognostic epigenetic gene patterns in breast cancer. …”
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Enhancing Cloud Job Failure Prediction With a Novel Multilayer Voting-Based Framework by Ahmed Elkaradawy, Ayman Elshenawy, Hany Harb

“…To address this challenge, researchers have progressively developed machine learning and deep learning techniques that examine cloud logs to identify patterns linked to such failures. …”
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Application of Discrete Element Method to Potato Harvesting Machinery: A Review by Yuanman Yue, Qian Zhang, Boyang Dong, Jin Li

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Landslide data sample augmentation and landslide susceptibility analysis in Nyingchi City based on the MCMC model by Lianchen Liu, Peiqing Wang, Libin Su, Feng Li

“…The quality of the generated samples was validated using a Support Vector Machine (SVM) classifier. Further sensitivity analysis and susceptibility modeling were conducted using both the original and augmented datasets. …”
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Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures by Omar Musbahi, MSc, ChM, Savvas Hadjixenophontos, MEng, Saran S. Gill, Iris Soteriou, Bsc, Kyriacos Pouris, Bsc, Takuro Ueno, PhD, Justin P. Cobb, MCh

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A 36-year geospatial analysis of urbanization dynamics and surface urban heat island effect: Case study of the Bangkok Metropolitan Region by Nattapong Puttanapong, Nithima Nuengjumnong, JoJinda SaeJung, Sitthisak Moukomla

“…(3) How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning? …”
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Neural network analysis of mortality risk predictors in patients after acute coronary syndrome by D. A. Shvets, A. Yu. Karasev, M. V. Smolyakov, S. V. Povetkin, V. I. Vishnevsky

“…An advantage of CNN is its ability to analyze patterns over time using recurrent neural networks.Conclusion. …”
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Vulnerability Time Series Forecasting: A Comparative Study of Hierarchical and Non-Hierarchical Approaches by Juscimara G. Avelino, Bruna A. O. Brito, Thiago T. de Oliveira, Jean M. M. de Lima, Andre M. Gurgel, Ramon S. Malaquias, Itamir de M. B. Filho

“…The proposed methodology aims to deal with the complexity of the data, allowing a hierarchical structure to understand and capture the interdependencies and patterns among different levels more completely. The evaluation is carried out with different ML models, such as LSTM, RNN, MLP, among others, comparing the performance of hierarchical and non-hierarchical approaches. …”
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Automated Cough Analysis with Convolutional Recurrent Neural Network by Yiping Wang, Mustafaa Wahab, Tianqi Hong, Kyle Molinari, Gail M. Gauvreau, Ruth P. Cusack, Zhen Gao, Imran Satia, Qiyin Fang

“…In this study, we developed a machine learning model for the detection and classification of cough sounds. …”
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Deep learning model using continuous skin temperature data predicts labor onset by Chinmai Basavaraj, Azure D. Grant, Shravan G. Aras, Elise N. Erickson

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Enterotype-stratified gut microbial signatures in MASLD and cirrhosis based on integrated microbiome data by Heng Yuan, Heng Yuan, Junyu Zhou, Junyu Zhou, Xuangao Wu, Shiwei Wang, Sunmin Park, Sunmin Park

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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…The use of ML enables the analysis of large datasets, the identification of complex patterns, and can save time and reduce costs compared to conventional approaches. …”
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Integrative radiomics analyses identify universal signature for predicting prognosis and therapeutic vulnerabilities across primary and secondary liver cancers: A multi-cohort stud... by Hongjie Xin, Qianwei Lai, Yanping Liu, Naying Liao, Ying Wang, Bihong Liao, Keyang Zhou, Yuchen Zhou, Yang Bai, Zhihua Chen, Yuanping Zhou

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Hadron Identification Prospects with Granular Calorimeters by Andrea De Vita, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas R. Gauger, Ralf Keidel, Jan Kieseler, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore

“…The analysis focuses on the impact of calorimeter granularity by progressively merging detector cells and extracting features like energy deposition patterns and timing information. Two machine learning approaches, XGBoost and fully connected deep neural networks, were employed to assess the classification performance across particle pairs. …”
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Feasibility Assessment of an Optically Powered Digital Retinal Prosthesis Architecture for Retinal Ganglion Cell Stimulation by William Lemaire, Maher Benhouria, Konin Koua, Wei Tong, Gabriel Martin-Hardy, Melanie Stamp, Kumaravelu Ganesan, Louis-Philippe Gauthier, Marwan Besrour, Arman Ahnood, David John Garrett, Sebastien Roy, Michael R. Ibbotson, Steven Prawer, Rejean Fontaine

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