Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…In recent years, the rapid development of artificial intelligence has opened up a new opportunity for data prediction. In this study, utilizing the EGM2008 satellite gravity model, we conducted a comprehensive analysis of three machine learning algorithms—random forest, support vector machine, and recurrent neural network—and compared their performances against the traditional Kriging interpolation method. …”
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Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation by Dominik Vondráček, Zdeněk Padovec, Tomáš Mareš, Nirupam Chakraborti

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Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei

“…EffiGRU-GhostNet integrates Gated Recurrent Units (GRU) with the GhostNet architecture, optimized through Principal Component Analysis with Locality Preserving Projections (PCA-LLP) to handle large-scale data effectively. …”
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Prediction of dialysis adequacy using data-driven machine learning algorithms by Yi-Chen Liu, Ji-Ping Qing, Rong Li, Juan Chang, Li-Xia Xu

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Clinical Big Data and Deep Learning: Applications, Challenges, and Future Outlooks by Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang

“…This article presents a comprehensive overview of studies that employ deep learning methods to deal with clinical data. Firstly, based on the analysis of the characteristics of clinical data, various types of clinical data (e.g., medical images, clinical notes, lab results, vital signs, and demographic informatics) are discussed and details provided of some public clinical datasets. …”
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Detection of Banana Diseases Based on Landsat-8 Data and Machine Learning by Renata Retkute, Kathleen S. Crew, John E. Thomas, Christopher A. Gilligan

“…Recent outbreaks of banana diseases are threatening the global banana industry and smallholder livelihoods. Remote sensing data offer the potential to detect the presence of disease, but formal analysis is needed to compare inferred disease data with observed disease data. …”
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SEM Deep Learning Multiclass Noise Level Classification With Data Augmentation by Kai Liang Lew, Kok Swee Sim, Shing Chiang Tan

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Deep learning prediction of mammographic breast density using screening data by Chen Chen, Enyu Wang, Vicky Yang Wang, Xiayi Chen, Bojian Feng, Ruxuan Yan, Lingying Zhu, Dong Xu

“…A retrospective analysis was conducted using data collected from Taizhou Cancer Hospital over a period from January 2015 to December 2020. …”
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Basic Research on the Development of an Automatic Heart Sound Diagnosis System - Analysis of Heart Sounds for Learning Policy and Experiment for the Prototype of the Auscultation P... by Hirotoshi Hishida, Koichi Tokuuye, Keiko Hishida, Hayato Tojo, Yasuhiro Hishida, Tomomi Koide

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Research on Park Perception and Understanding Methods Based on Multimodal Text–Image Data and Bidirectional Attention Mechanism by Kangen Chen, Xiuhong Lin, Tao Xia, Rushan Bai

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Enhancing Recognition and Categorization of Skin Lesions with Tailored Deep Convolutional Networks and Robust Data Augmentation Techniques by Syed Ibrar Hussain, Elena Toscano

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Solar Flare Prediction Using Multivariate Time Series of Photospheric Magnetic Field Parameters: A Comparative Analysis of Vector, Time Series, and Graph Data Representations by Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

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Data-driven integration of synthetic representative volume elements and machine learning for improved microstructure-property linkage and material performance in ceramics by Mohammad Rezasefat, James Hogan

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Decentralized big data mining: federated learning for clustering youth tobacco use in India by Rahul Haripriya, Nilay Khare, Manish Pandey, Sreemoyee Biswas

“…Federated learning enables collaborative analysis across different regions by sharing only model parameters rather than raw data, thus enhancing privacy. …”
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A Novel Multi-Task Learning Framework for Interval-Valued Carbon Price Forecasting Using Online News and Search Engine Data by Dinggao Liu, Liuqing Wang, Shuo Lin, Zhenpeng Tang

“…To address the need for interval-valued time series modeling and forecasting in the carbon market, this paper proposes a Transformer-based multi-task learning framework that integrates online news and search engine data information to forecast interval-valued EU carbon allowance futures prices. …”
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A Unified Surrogate Framework for Data-Driven Reliability Analysis of Mechanical Systems from Low to Multi-DOF by Lun Shao, Alexandre Saidi, Abdel-Malek Zine, Mohamed Ichchou

“…The framework is further extended to a 10-DOF structure, and the simulation results confirm that machine learning-based models are highly effective for large-scale reliability analysis. …”
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Slip Tendency Analysis From Sparse Stress and Satellite Data Using Physics‐Guided Deep Neural Networks by Thomas Poulet, Pouria Behnoudfar

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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

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Network-based analyses of multiomics data in biomedicine by Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie

“…This review will present various existing approaches in using network representations and analysis of data in multiomics in the framework of deep learning and machine learning approaches, subdivided into supervised and unsupervised approaches, to identify benefits and drawbacks of various approaches as well as the possible next steps for the field.…”
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