Comparative Analysis of Control Strategies for Microgrid Energy Management with a Focus on Reinforcement Learning by Parisa Mohammadi, Razieh Darshi, Saeed Shamaghdari, Pierluigi Siano

“…Traditional methods, including classical, metaheuristic, model predictive, stochastic, and robust control techniques, have been extensively studied. …”
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The Advanced Actuarial Data Science Based AI-Driven Solutions for Automated Loss Reserving Under IFRS 17 in Non-Life Insurance by Brighton Mahohoho, Charles Chimedza, Florance Matarise, Sheunesu Munyira

“…This AI-integrated approach significantly improves predictive accuracy, operational efficiency, and strategic decision-making, offering a scalable solution for the insurance industry. …”
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Quality monitoring of hybrid welding processes: A comprehensive review by Solomon Habtamu Tessema, Dariusz Bismor

“…Furthermore, the review highlights the integration of sensor data with AI/ML algorithms and digital twin technologies, enhancing the capabilities of quality monitoring systems. …”
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Application of a Hybrid Model for Data Analysis in Hydroponic Systems by Kuanysh Bakirov, Jamalbek Tussupov, Akhmet Tussupov, Ibraheem Shayea, Aruzhan Shoman

“…Experimental evaluation demonstrated superior predictive performance by using XGBoost, achieving an accuracy and F1-score of 97.88%, ROC-AUC of 99.99%, and computational efficiency (training completed in 2.3 s), outperforming RandomForest and GradientBoosting algorithms. …”
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Matrix Metalloproteinase-9 is associated with tumor microenvironment remodeling of bladder cancer by Fang Fang, Tiange Wu, Mengxue Wang, Wenchao Li, Zonghao You, Ming Chen, Han Guan

“…Matrix Metalloproteinase-9 (MMP9) was identified as a predictive biomarker related to immune microenvironment. …”
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Implications of artificial intelligence in periodontal treatment maintenance: a scoping review by Raafat Musief Sarakbi, Sudhir Rama Varma, Sudhir Rama Varma, Lovely Muthiah Annamma, Vinay Sivaswamy, Vinay Sivaswamy

“…Additionally, AI facilitated predictive analytics for disease progression and personalized treatment strategies. …”
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Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population by Aaro Tupasela, Juanita Devis Clavijo, Marjut Salokannel, Christoph Fink

“…In this article, we report on the main challenges encountered during the implementation of the URBANAGE project, and the development of the components for big data analytics, visualisations, predictive algorithms and simulation. Using examples from three European locations – Helsinki, Flanders and Santander – we describe and discuss how we can gather personal data related to the daily lives of older people in terms of the existing privacy and data protection laws in the EU. …”
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Effective tweets classification for disaster crisis based on ensemble of classifiers by Christopher Ifeanyi Eke, Kholoud Maswadi, Musa Phiri, Mulenga, Mohammad Imran, Dekera Kwaghtyo, Akeremale Olusola Collins

“…The proposed approach demonstrates not only high predictive capacity but also scalability for real-time tweet filtering during emergencies. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…The need for frequent follow-up, including invasive procedures like cystoscopy, repetitive procedures like transurethral resection of bladder tumors and intravesical instillation therapy in non-muscle invasive stages, as well as systemic treatment with or without radical local treatment in advanced stages, makes bladder cancer one of the most expensive cancers to treat. Prognostic and predictive biomarkers have the potential to fundamentally change bladder cancer treatment algorithms, which may result in improved patient comfort and oncological outcomes and may also decrease the socioeconomic burden of the disease. …”
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The Fractality of Sentiment Arcs for Literary Quality Assessment: the Case of Nobel Laureates by Yuri Bizzoni, Pascale Moreira, Mads Rosendahl Thomsen, Kristoffer L. Nielbo

“…To test this hypothesis, we present the results from two studies: (i) a probability distribution test, where we compute the probability of seeing a title from a Nobel laureate at different levels of arc fractality; (ii) a classification test, where we use several machine learning algorithms to measure the predictive power of both sentiment arcs and their fractality measure. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  …”
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Aligned in Human Dignity? Parallel Anthropological Aspects of EU Tech Regulation and Pope Francis’ Teaching on AI by Bernát Török, Ádám Darabos

“…We will highlight four concrete challenges posed by artificial intelligence to the human person (profiling, predictive algorithms, human intervention and manipulation), to which the legislation of the European Union has responded partly on anthropological grounds. …”
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Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…All the three well-trained models demonstrated robust predictive capabilities for ultimate tensile strength (UTS), elongation (EL), and yield strength (YS). …”
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Exosomal microRNA signatures in youth at clinical high risk for bipolar disorder by Xinyu Meng, Shengmin Zhang, Yingzhen Xu, Zaohui Ma, Shuzhe Zhou, Yantao Ma, Hong Ma, Xin Yu, Lili Guan

“…Using machine-learning algorithms, target miRNAs were selected from differentially expressed candidates. …”
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Constitutional-Legal Aspect of Creating Large Language Models: the Problem of Digital Inequality and Linguistic Discrimination by I. G. Ilin

“…While direct forms of discrimination can be detected in predictive algorithms, generative models create more subtle but no less significant cumulative effects. …”
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Multimodal machine learning-based model for differentiating nontuberculous mycobacteria from mycobacterium tuberculosis by Hong-ling Li, Ri-zeng Zhi, Hua-sheng Liu, Mei Wang, Si-jie Yu

“…The multimodal model contained age, IL-6, and the 2 radiomics features, and the optimal model was from LightGBM algorithm. The optimal multimodal model had the highest AUC value, accuracy, sensitivity, and negative predictive value compared with the optimal clinical or radiomics models, and its’ favorable performance was also verified in the external test dataset (accuracy = 0.745, sensitivity = 0.900). …”
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The future of 3D printing in instrumented implantable polymer meta-stents by C. Brosseau, G. Nocchiero, J. Ville

“…Thirdly, virtual replica digital twin technology can facilitate personalized stent design based on individual patient characteristics, medical history, and real-time physiological data. This new predictive analysis in healthcare systems relies largely on the use of deep learning algorithms, appropriate for managing massive data integration. …”
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Forecast of hydrocarbon losses in deposits during the development of gas condensate fields by R. K. Dobrolyubova, E. I. Inyakina, I. I. Krasnov, V. V. Inyakin, A. F. Semenenko

“…The data of the conducted studies allow us to formulate predictive recommendations on changes in the properties of fluids and the condensate recovery coefficient.…”
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Assessing Climate Change Impacts on Cropland and Greenhouse Gas Emissions Using Remote Sensing and Machine Learning by Nehir Uyar, Azize Uyar

“…The results revealed a strong correlation between agricultural expansion and increased C and N₂O emissions, with RF and GBT models demonstrating superior predictive accuracy. Specifically, GBT and RF achieved the highest R² value (0.71, 0.59) and the lowest error metrics in modeling emissions, whereas SVM performed poorly across all cases. …”
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Machine learning and deep learning in medicine and neuroimaging by Iván Sánchez Fernández, Jurriaan M. Peters

“…Machine learning is starting to be successfully applied to several areas of medicine, including predictive analytics, decision support, natural language processing of free‐text notes, and automatic interpretation of electrophysiological recordings. …”
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