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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions
Published 2024-12-01“…More research in trustworthy AI, standardizing AI-driven methods, legislations for robust privacy protection amongst others is emphasized. …”
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GDDKIA xml service, road traffic incidents data: availability and quality research
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Visual analysis of research trends in diabetes-associated dry eye via bibliometrics
Published 2025-09-01“…Building risk prediction models using machine learning algorithms is a promising future research direction, enabling physicians to identify high-risk individuals and implement early interventions.…”
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Research on the Aided Diagnosis Method of Diseases Based on Domain Semantic Knowledge Bases
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Research trends and prospects in global riverine carbon fluxes: A bibliometric analysis
Published 2025-01-01“…The analysis of keywords demonstrates that current study on RCFs mainly focus on monitoring the fluxes of multiple forms of carbon in the fluvial systems, modeling the fluxes of riverine carbon at larger scales, elaborating the complex biogeochemical processes of riverine carbon transport. Future research should further investigate the index quantification, scaling algorithms, and modeling framework of RCFs. …”
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Research progress on shale gas productivity evaluation: concepts, methods and future directions
Published 2025-06-01“…Based on these findings, future research should focus on integrating shale gas flow mechanisms at both micro and macro scales. …”
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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects
Published 2025-04-01“…Moreover, AI's evolving role in genetic research supports personalized NTD prevention strategies and enhances public awareness through AI-generated health messages. …”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels
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Assessment of Machine Learning Algorithms in Short-term Forecasting of PM10 and PM2.5 Concentrations in Selected Polish Agglomerations
Published 2021-03-01“…We tested four ML models: AIC-based stepwise regression, two tree-based algorithms (random forests and XGBoost), and neural networks. …”
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Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review
Published 2025-02-01“…Convolutional neural networks were most prevalent, demonstrating high performance, followed by gradient- and decision tree-based algorithms. Other algorithms, though underrepresented, showed promise. …”
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