AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness by Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan, Attasit Wiangkham

“…Furthermore, this approach provides a pathway for utilizing AI in other engineering domains where data sets are limited.…”
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Predicting Olive Tree Chlorophyll Fluorescence Using Explainable AI with Sentinel-2 Imagery in Mediterranean Environment by Leonardo Costanza, Beatriz Lorente, Francisco Pedrero Salcedo, Francesco Pasanisi, Vincenzo Giannico, Francesca Ardito, Carlota María Martí Martínez, Simone Pietro Garofalo

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Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment by Ihtisham Bukhari, Ihtisham Bukhari, Mengxue Li, Guangyuan Li, Jixuan Xu, Pengyuan Zheng, Xiufeng Chu, Xiufeng Chu

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Nursing Educators’ Perspectives on the Integration of Artificial Intelligence Into Academic Settings by Moustaq Karim Khan Rony MSS, MPH, RN, Sumon Ahmad MPH, RN, Sabren Mukta Tanha MPH, RN, Dipak Chandra Das MSS, Mosammat Ruma Akter MSN, RN, Mst. Amena Khatun MPH, RN, Most. Hasina Begum MSN, RN, Md Ibrahim Khalil MSS, RN, Umme Rabeya Peu MSS, RN, Mst. Rina Parvin BSN, RN, Daifallah M Alrazeeni PhD, Fazila Akter MSc, RN

“…Background The integration of artificial intelligence (AI) into education has the potential to revolutionize teaching and learning practices, especially in nursing education, which combines theoretical and practical knowledge. …”
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A Novel Deeply-Learned Image Quality Analysis Algorithm for Clustering by Zhongzhe Chen, Xing Gao

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Hybridization of metaheuristic algorithms for resource scheduling in distributed robotic control system by P. Anand Raj, M. Rajakumaran, S. Palani Murugan, S. Senthilkumar

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The impact of algorithm awareness training on competent interaction with intelligent voice assistants by André Markus, Maximilian Baumann, Jan Pfister, Andreas Hotho, Astrid Carolus, Carolin Wienrich

“…Abstract Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. …”
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Evaluating Critical Success Factors in AI-Driven Drug Discovery Using AHP: A Strategic Framework for Optimization by Amir Mohamed Talib, Areen Metib Al-Hgaish, Rodziah Binti Atan, Abdulaziz Alshammari, Fahad Omar Alomary, Razali Yaakob, Abdulaziz Alsahli, Mohd Hafeez Osman

“…This research contributes to strategic AI adoption by addressing data inconsistencies, algorithmic bias, and scalability limitations. …”
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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis... by Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer

“…Summary: Background: Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. …”
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Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions by Elias Dritsas, Maria Trigka

“…This survey examines the application of key AI techniques, particularly machine learning (ML), natural language processing (NLP), network science, and explainable AI (XAI), in addressing domain-specific challenges in empirical research. …”
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Artificial intelligence in clinical decision support and the prediction of adverse events by S. P. Oei, T. H. G. F. Bakkes, M. Mischi, R. A. Bouwman, R. A. Bouwman, R. J. G. van Sloun, S. Turco

“…Biases in data acquisition, such as population shifts and data scarcity, threaten the generalizability of AI-based CDS algorithms across different healthcare centers. …”
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A review of recent artificial intelligence for traditional medicine by Chengbin Hou, Yanzhuo Gao, Xinyu Lin, Jinchao Wu, Ning Li, Hairong Lv, William Cheng-Chung Chu

“…By leveraging advanced algorithms and models, AI can improve decision-making efficiency, optimize diagnosis accuracy, enhance patient experience, and reduce costs. …”
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Impact of EU Laws on AI Adoption in Smart Grids: A Review of Regulatory Barriers, Technological Challenges, and Stakeholder Benefits by Bo Nørregaard Jørgensen, Saraswathy Shamini Gunasekaran, Zheng Grace Ma

“…The analysis delves into regulatory barriers such as data protection requirements, algorithmic transparency mandates, and liability concerns that can limit the scope and scale of AI deployment. …”
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A secure IoT-edge architecture with data-driven AI techniques for early detection of cyber threats in healthcare by Mamta Kumari, Mahendra Gaikwad, Salim A. Chavan

“…Integrating AI-driven intrusion detection systems is crucial for safeguarding IoMT against evolving cyber threats, ensuring patient safety and data privacy. …”
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AI-Based Prediction of Visual Performance in Rhythmic Gymnasts Using Eye-Tracking Data and Decision Tree Models by Ricardo Bernardez-Vilaboa, F. Javier Povedano-Montero, José Ramon Trillo, Alicia Ruiz-Pomeda, Gema Martínez-Florentín, Juan E. Cedrún-Sánchez

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Enhancing Radiologist Efficiency with AI: A Multi-Reader Multi-Case Study on Aortic Dissection Detection and Prioritization by Martina Cotena, Angela Ayobi, Colin Zuchowski, Jacqueline C. Junn, Brent D. Weinberg, Peter D. Chang, Daniel S. Chow, Jennifer E. Soun, Mar Roca-Sogorb, Yasmina Chaibi, Sarah Quenet

“…Conclusions: The integration of a DL-based algorithm for AD detection on chest CTAs significantly reduces both the STAT and IT. …”
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A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade by Attila Kovari

“…This review examines the current state of integration and impact of AI-enhanced collaborative learning in the higher education sector. …”
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SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…This study addresses critical security and efficiency challenges in M2M communication within the context of IoT. SAFE-CAST integrates several innovative components: (1) a federated learning approach using Lloyd’s K-means algorithm for secure clustering, (2) a quality diversity optimization algorithm (QDOA) for secure channel selection, (3) a dynamic trust management system utilizing blockchain technology, and (4) an adaptive multi-agent reinforcement learning for context-aware transmission scheme (AMARLCAT) to minimize latency and improve scalability. …”
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Fusing Machine Learning and AI to Create a Framework for Employee Well-Being in the Era of Industry 5.0 by Cosmina-Mihaela Rosca, Adrian Stancu

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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…This research presents an innovative approach to enhance altitude estimation accuracy for UAVs weighing under 2 kg without cameras, utilizing advanced AI Deep Learning algorithms. The primary novelty of this study lies in its unique integration of unsupervised and supervised learning techniques. …”
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