Linear Diophantine Uncertain Linguistic Power Einstein Aggregation Operators and Their Applications to Multiattribute Decision Making by Tahir Mahmood, Izatmand, Zeeshan Ali, Kifayat Ullah, Qaisar Khan, Ahmed Alsanad, Mogeeb A. A. Mosleh

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Predicting Traffic Accident Risk in Seoul Metropolitan City: A Dataset Construction Approach by Ji-Woong Yang, Hyeon-Jin Jung, Tae-Wook Kim, Han-Jin Lee, Ellen J. Hong

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Semantic Features-Based Discourse Analysis Using Deceptive and Real Text Reviews by Husam M. Alawadh, Amerah Alabrah, Talha Meraj, Hafiz Tayyab Rauf

“…To rectify the problem, many artificial intelligence–based studies have performed discourse analysis on reviews to validate their genuineness. …”
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TS-PAID: A Two-Stage PUF-Based Lightweight Authentication Protocol for Internet of Drones by Shehzad Ashraf Chaudhry, Azeem Irshad, Bander A. Alzahrani, Ahmad Alhindi, Mohd Shariq, Ashok Kumar Das

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Application of Radial Basis Function Neural Network Coupling Particle Swarm Optimization Algorithm to Classification of Saudi Arabia Stock Returns by Khudhayr A. Rashedi, Mohd Tahir Ismail, Nawaf N. Hamadneh, S. AL Wadi, Jamil J. Jaber, Muhammad Tahir

“…Artificial intelligence (AI) based business process optimization has a significant impact on a country’s economic development. …”
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An ultrasonic-AI hybrid approach for predicting void defects in concrete-filled steel tubes via enhanced XGBoost with Bayesian optimization by Shuai Wan, Shipan Li, Zheng Chen, Yunchao Tang

“…This hybrid approach offers high efficiency and accuracy for void defect detection in CFST, providing a novel solution that leverages the strengths of both traditional ultrasonic methods and artificial intelligence algorithms. The method not only detects the presence of void defects but also quantifies their extent, advancing CFST inspection from qualitative analysis to quantitative assessment.…”
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Research progress of MRI-based radiomics in hepatocellular carcinoma by Xiao-Yun Xie, Rong Chen

“…Key search terms included Hepatocellular carcinoma, HCC, Liver cancer, Magnetic resonance imaging, MRI, radiomics, deep learning, machine learning, and artificial intelligence.ResultsA comprehensive analysis of 93 articles underscores the efficacy of MRI radiomics, a noninvasive imaging analysis modality, across various facets of HCC management. …”
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A generative deep neural network for pan-digestive tract cancer survival analysis by Lekai Xu, Tianjun Lan, Yiqian Huang, Liansheng Wang, Junqi Lin, Xinpeng Song, Hui Tang, Haotian Cao, Hua Chai

“…With the rapid advancement of artificial intelligence, various machine learning algorithms have been successfully applied in this field. …”
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Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation by Zhan Wang, Mwamba Kasongo Dahouda, Hyoseong Hwang, Inwhee Joe

“…To enhance the interpretability of the results, explainable artificial intelligence (XAI) techniques are incorporated, specifically shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), to identify which features have the most impact on detected anomalies. …”
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Metastatic brain tumors: from development to cutting‐edge treatment by Guilong Tanzhu, Liu Chen, Jiaoyang Ning, Wenxiang Xue, Ce Wang, Gang Xiao, Jie Yang, Rongrong Zhou

“…Additionally, we summarize multiomics evidence on the mechanisms of tumor occurrence and development in the era of artificial intelligence and discuss the role of the tumor microenvironment. …”
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Wind Energy Resource Prediction and Optimal Storage Sizing to Guarantee Dispatchability: A Case Study in the Kenyan Power Grid by Hampfrey Odero, Cyrus Wekesa, George Irungu

“…To mitigate these and to ensure proper planning of the system operations, accurate and faster prediction of the generation output of the wind energy resources and optimal design and sizing of storage for the large-scale wind energy integration into the grid are of paramount importance. Artificial intelligence (AI) and metaheuristic techniques have proven to be efficient and robust in offering solutions to complex nonlinear prediction and optimization problems. …”
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Accessible AI Diagnostics and Lightweight Brain Tumor Detection on Medical Edge Devices by Akmalbek Abdusalomov, Sanjar Mirzakhalilov, Sabina Umirzakova, Abror Shavkatovich Buriboev, Azizjon Meliboev, Bahodir Muminov, Heung Seok Jeon

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Hematoxylin and Eosin-stained whole slide image dataset annotated for skin tissue segmentationMendeley Data by Anum Abdul Salam, Muhammad Zeeshan Asaf, Muhammad Usman Akram, Noah Musolff, Samavia Khan, Bassem Rafiq, Babar Rao

“…With the advent of Artificial Intelligence (AI) and technology, the use of automated disease diagnosis systems has increased significantly. …”
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Towards Personalized Radiotherapy in Pelvic Cancer: Patient-Related Risk Factors for Late Radiation Toxicity by Anna C. Nuijens, Arlene L. Oei, Nicolaas A. P. Franken, Coen R. N. Rasch, Lukas J. A. Stalpers

“…Single-nucleotide polymorphisms (SNPs) likely elevate the risk in specific combinations. Advances in artificial intelligence now allow for the identification of SNP patterns from large datasets, supporting the development of polygenic risk scores. …”
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Survey on Lie Group Machine Learning by Mei Lu, Fanzhang Li

“…Lie group machine learning is recognized as the theoretical basis of brain intelligence, brain learning, higher machine learning, and higher artificial intelligence. Sample sets of Lie group matrices are widely available in practical applications. …”
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A review of quantum communication and information networks with advanced cryptographic applications using machine learning, deep learning techniques by R. Ramya, P. Kumar, D. Dhanasekaran, R. Satheesh Kumar, S. Amithesh Sharavan

“…Quantum memory enables storage and retrieval of quantum information, while quantum entanglement generators generate entangled photon pairs. Artificial intelligence and machine learning have significantly improved the efficacy and security of quantum communication. …”
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Hybridization of stochastic hydrological models and machine learning methods for improving rainfall-runoff modeling by Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick K. Ronoh, Stephen E. Moore

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Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem by Lu Ye, Saadya Fahad Jabbar, Musaddak M. Abdul Zahra, Mou Leong Tan

“…Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. …”
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Recent Developments on Novel 2D Materials for Emerging Neuromorphic Computing Devices by Muhammad Hamza Pervez, Ehsan Elahi, Muhammad Asghar Khan, Muhammad Nasim, Muhammad Asim, Arslan Rehmat, Malik Abdul Rehman, Mohammed A. Assiri, Shania Rehman, Jonghwa Eom, Muhammad Farooq Khan

“…The rapid advancement of artificial intelligent and information technology has led to a critical need for extremely low power consumption and excellent efficiency. …”
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The research progress of biologics in elderly-onset rheumatoid arthritis (EORA) by Yujie Li, Yifan Liu, Yanhui Tian, Huimin Gu, Qingliang Meng, Jiakang Cui, Junfu Ma

“…With the rapid progress of precision medicine and artificial intelligence (AI) technologies, gene profiling, biomarker analysis, and AI-assisted decision-making are gradually steering EORA treatment towards more personalized and precise strategies. …”
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