Predicting biochar yield from biomass pyrolysis: A comprehensive data-driven approach using machine learning and SHAP analysis by Walid Abdelfattah, Munthar Kadhim Abosaoda, Krunal Vaghela, Gowrishankar J, Prabhat Kumar Sahu, Kamred Udham Singh, R. Sivaranjani, Rohit Chauhan, Siya Singla, Samim Sherzod

“…This study employs a comprehensive data-driven approach to predict biochar yield using machine learning algorithms. …”
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Multimodal CustOmics: A unified and interpretable multi-task deep learning framework for multimodal integrative data analysis in oncology. by Hakim Benkirane, Maria Vakalopoulou, David Planchard, Julien Adam, Ken Olaussen, Stefan Michiels, Paul-Henry Cournède

“…Each modality operates at distinct biological levels, introducing substantial correlations between and within data sources. In response to these challenges, we propose a novel deep-learning-based approach designed to represent multi-omics & histopathology data for precision medicine in a readily interpretable manner. …”
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Postpartum Haemorrhage Risk Prediction Model Developed by Machine Learning Algorithms: A Single-Centre Retrospective Analysis of Clinical Data by Wenhuan Wang, Chanchan Liao, Hongping Zhang, Yanjun Hu

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The use of outcome data from quality registries to learn and improve; a Dutch nationwide quantitative analysis in five disease areas by Stacey R. Slingerland, Lise A. M. Moers, Niki M. Medendorp, Paul B. van der Nat, Lineke Derks, Marijke J. C. Timmermans, Nicolette de Keizer, Marc ten Dam, Geke Denissen, Dennis van Veghel

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Regional Glacier Mapping and Change Analysis in the Gangshika Region of Qilian Mountain Based on Deep Learning and Satellite Data Time-Series by Lihao Chen, Wei Xu, Zhen Cao, Jiaqi Zhang, Zhizhong Kang

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Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

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Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris, Panagiotis Stefanidis

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Multilingual competency and academic performance: a machine learning-based analysis of the 2022/2023 Somaliland national primary exam data by Jibril Abdikadir Ali, Mustafe Khadar Abdi, Tawakal Abdi Ali, Abdisalan Hassan Muse, Mukhtar Abdi Omar, Mukhtaar Axmed Cumar

“…The analysis revealed demographic imbalances, with data predominantly from urban (90.8%) and private school (57.3%) students. …”
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Enhanced soil organic carbon mapping in Gannan’s alpine meadows: A comparative analysis of machine learning models and satellite data by Xingyu Liu, Meiling Zhang, Ziming Ma

“…Findings indicate: (1) The GBDT model surpassed RF and XGBoost in predictive accuracy; (2) Integrating data from different satellite sensors improved the soil prediction models; (3) The GBDT model, incorporating data from Sentinel-1, Sentinel-2, and Digital Elevation Model (DEM), achieved the highest accuracy from the test sets (R2 = 0.5702 RMSE = 4.1557 kg C m−2, MAE = 3.1110 kg C m−2, LCCC = 0.7689), with significant enhancements from Sentinel-1; (4) DEM data were crucial in predicting SOCD, followed by Sentinel-2 and Sentinel-1. …”
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Bidders Recommender for Public Procurement Auctions Using Machine Learning: Data Analysis, Algorithm, and Case Study with Tenders from Spain by Manuel J. García Rodríguez, Vicente Rodríguez Montequín, Francisco Ortega Fernández, Joaquín M. Villanueva Balsera

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Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…<b>Methods:</b> This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. …”
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Prescriptive Predictors of Mindfulness Ecological Momentary Intervention for Social Anxiety Disorder: Machine Learning Analysis of Randomized Controlled Trial Data by Nur Hani Zainal, Hui Han Tan, Ryan Yee Shiun Hong, Michelle Gayle Newman

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Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in Transcriptomics, Proteomics, and Metabolomics by Pedro H. Godoy Sanches, Nicolly Clemente de Melo, Andreia M. Porcari, Lucas Miguel de Carvalho

“…In this article, we review strategies for integrating transcriptomics, proteomics, and metabolomics data, including co-expression analysis, metabolite–gene networks, constraint-based models, pathway enrichment analysis, and interactome analysis. …”
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Advancing Built-Up Area Monitoring Through Multi-Temporal Satellite Data Fusion and Machine Learning-Based Geospatial Analysis by Alessandro Vitale, Francesco Lamonaca

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Data-Driven Analysis of Fluorescence Lifetime Imaging Experiments: Unraveling the Signal/Stress Relationship of Polluted Microalgae Cells with Machine Learning by Erwan Privat, Ilaria Fortunati, Camilla Ferrante, Sergio Rampino, Antonino Polimeno

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Spatial Distribution Pattern of Forests in Yunnan Province in 2022: Analysis Based on Multi-Source Remote Sensing Data and Machine Learning by Guangyang Li, Hongyan Lai, Bangqian Chen, Xiong Yin, Weili Kou, Zhixiang Wu, Zongzhu Chen, Guizhen Wang

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Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…In fact, it is responsible for significant developments in the field of precision medicine, as well as in preventive and predictive medicine. The analysis focuses on a large volume of clinical data and patient characteristics of those who underwent assisted reproduction treatments. …”
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Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability. by Xiao Zhou, Sanchita Kedia, Ran Meng, Mark Gerstein

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From bed to bench and back again: Challenges facing deployment of intracranial pressure data analysis in clinical environments by Laura Moss, Martin Shaw, Ian Piper, Christopher Hawthorne

“…Further, the ability to refine models using ongoing patient data collection is rare. In this paper we identify and discuss the challenges faced when converting insight from ICP data analysis into deployable tools at the patient bedside. …”
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Fusion of Geochemical Data and Remote Sensing Data Based on Convolutional Neural Network by Shi Bai, Jie Zhao, Tianhan Yu, Yunqing Shao

“…The fusion of these two types of datasets can provide richer and more accurate information for geoscience analysis. But the existing remote sensing&#x2013;geochemical data fusion methods have problems; there is a big gap between the two kinds of data in resolution. …”
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