Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Experimental results demonstrate a substantial reduction in electricity costs for consumers by an average of 25% and a decrease in carbon dioxide (CO2) emissions by 40 tons annually. …”
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Deep Learning Applications in Ionospheric Modeling: Progress, Challenges, and Opportunities by Renzhong Zhang, Haorui Li, Yunxiao Shen, Jiayi Yang, Wang Li, Dongsheng Zhao, Andong Hu

“…Looking ahead, research will focus on developing hybrid models that integrate physical modeling with deep learning, exploring adaptive learning algorithms and multi-modal data fusion techniques to enhance long-term predictive capabilities, particularly in addressing the impact of climate change on the ionosphere. …”
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Transfer Learning-Empowered Physical Layer Security in Aerial Reconfigurable Intelligent Surfaces-Based Mobile Networks by Yosefine Triwidyastuti, Tri Nhu Do, Ridho Hendra Yoga Perdana, Kyusung Shim, Beongku An

“…To address these challenges, we develop robust algorithms for optimizing the phase-shift configurations of RIS. …”
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Intelligent energy management of microgrids using machine learning: Leveraging random forest models for solar and wind power by Hasanur Zaman Anonto, Md Ismail Hossain, Abu Shufian, Md. Shaoran Sayem, S M Tanvir Hassan Shovon, Protik Parvez Sheikh, Sadman Shahriar Alam

“…Integrating grid-stability measures, that is, voltage and frequency variation into the predictive model, the framework enhances the accuracy of the energy dispatch and storage plans. …”
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Exploring pesticide risk in autism via integrative machine learning and network toxicology by Ling Qi, Jingran Yang, Qiao Niu, Jianan Li

“…Each combination of 1–23 targets was used to construct predictive models using eight different machine learning algorithms. …”
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Unveiling Immune Response Mechanisms in Mpox Infection Through Machine Learning Analysis of Time Series Gene Expression Data by Qinglan Ma, Xianchao Zhou, Lei Chen, Kaiyan Feng, Yusheng Bao, Wei Guo, Tao Huang, Yu-Dong Cai

“…Then, the incremental feature selection method was applied to each list to extract key genes and build efficient prediction models and classification rules for each list. …”
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Methodology For Extracting Poplar Planted Fields From Very High-Resolution Imagery Using Object-Based Image Analysis and Feature Selection Strategy by E. O. Yilmaz, T. Kavzoglu, I. Colkesen, H. Tonbul, A. Teke

“…The most effective and contributing object features that assure high separability between landscape features were determined using a filter-based Chi-square algorithm for the prediction models constructed with SVM, RF, and RotFor classifiers. …”
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Latest Advancements in Credit Risk Assessment with Machine Learning and Deep Learning Techniques by Soni Umangbhai, Jethava Gordhan, Ganatra Amit

“…The goal is to help develop novel algorithms that outperform existing methods. Even a slight improvement in defaulter prediction rates could significantly influence society by saving millions for lenders.…”
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Optimal model-based insulin dosing strategy with offline and online optimization by Martin Dodek, Eva Miklovičová, Miroslav Halás

“…This paper presents the design of a model-based bolus calculator algorithm aimed at optimizing insulin therapy for patients with type 1 diabetes. …”
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Diagnostic Utility of ¹⁸F-FDG PET/CT in Infective Endocarditis by Corina-Ioana Anton, Alice-Elena Munteanu, Mihaela Raluca Mititelu, Militaru Alexandru Ștefan, Cosmin-Alexandru Buzilă, Adrian Streinu-Cercel

“…PET/CT reclassified 13 patients from possible to definite IE, demonstrating an overall sensitivity of 83.3%, specificity of 93.7%, positive predictive value (PPV) of 83.3%, and negative predictive value (NPV) of 93.7%. …”
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Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning by Junyang Ma, Junyang Ma, Shufu Hou, Xinxin Gu, Peng Guo, Jiankang Zhu

“…The nomogram constructed based on 8 genes with diagnostic value had good predictive performance.…”
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Comprehensive Review on the Control of Heat Pumps for Energy Flexibility in Distribution Networks by Gustavo L. Aschidamini, Mina Pavlovic, Bradley A. Reinholz, Malcolm S. Metcalfe, Taco Niet, Mariana Resener

“…Real-time optimization is achieved through model predictive control (MPC), which relies on a predictive model to optimize decisions over a time horizon, and reinforcement learning (RL), which takes a model-free approach by learning optimal strategies through direct interaction with the environment. …”
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Prognosis of unfavorable course of ulcerative colitis as indication for anticytokine therapy by A. Yu. Baranovsky, E. A. Kondrashina, A. G. Kharitonov

“…Aim of investigation. To outline predictive model for unfavorable course of ulcerative colitis (UC).Material and methods. …”
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Creation of a collection of different biological sample types from elderly patients to study the relationship of clinical, systemic, tissue and cellular biomarkers of accumulation... by A. G. Sorokina, Ya. A. Orlova, O. A. Grigorieva, E. S. Novoseletskaya, N. A. Basalova, N. A. Alexandrushkina, M. A. Vigovsky, K. I. Kirillova, A. V. Balatsky, L. M. Samokhodskaya, N. V. Danilova, U. D. Dyachkova, D. А. Fedotov, A. A. Akopyan, V. V. Kakotkin, D. A. Asratyan, Zh. A. Akopyan, A. Yu. Efimenko

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An introduction to causal discovery by Martin Huber

“…This survey provides an introduction to key concepts, algorithms, and applications of causal discovery from the perspectives of economics and social sciences. …”
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<b>The investigation of commonalities in human brain semantic representations across people and across languages</b><br> by Augusto Buchweitz

“…Recent studies on the organization of conceptual knowledge in the human brain have reported the remarkable ability to predict the word a person is thinking about, or the picture a person is seeing, from their brain activity. …”
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Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems by Rongke Nie, Xingyi Huang, Xiaoyu Tian, Shanshan Yu, Chunxia Dai, Xiaorui Zhang, Qin Fang

“…The results showed that the optimal NIR-based discriminative model, constructed with a Random Forest (RF) algorithm based on spectra preprocessed by the second-derivative (D2) denoising and a Competitive Adaptive Reweighted Sampling (CARS) algorithm, achieved a prediction set accuracy of 86.00%; the optimal soft X-ray imaging-based discriminative model, built with an RF algorithm using textural features extracted from images preprocessed by median filtering and a Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithm combined with gray-level co-occurrence matrix (GLCM) and gray-gradient co-occurrence matrix (GGCM) algorithms, reached a prediction set accuracy of 93.10%. …”
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Machine learning model for preoperative classification of stromal subtypes in salivary gland pleomorphic adenoma based on ultrasound histogram analysis by Huan-Zhong Su, Dao-Hui Yang, Long-Cheng Hong, Yu-Hui Wu, Kun Yu, Zuo-Bing Zhang, Xiao-Dong Zhang

“…The least absolute shrinkage and selection operator (LASSO) regression identified optimal features, which were then utilized to build predictive models using logistic regression (LR) and eight ML algorithms. …”
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Modeling the variables that influence substance consumption of people who experience homelessness in Colombia by Leandro González Támara, Sandra Patricia Barragán Moreno

“…A two-stage quantitative methodology was applied: (1) descriptive analysis of the demographic and socioeconomic characteristics of the homeless population, and (2) predictive modeling using random forest algorithms to identify key variables associated with substance use. …”
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Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…These obstacles were mitigated through the integration of algorithmically derived pseudo-rugosity and slope metrics as innovative proxies for seafloor complexity, significantly improving predictive performance. …”
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