geeSSEBI: Evaluating Actual Evapotranspiration Estimated with a Google Earth Engine Implementation of S-SEBI by Jerzy Piotr Kabala, Jose Antonio Sobrino, Virginia Crisafulli, Dražen Skoković, Giovanna Battipaglia

“…For decades, remote sensing data have been utilized to estimate ET, leading to the development of numerous algorithms. However, their application is still non-trivial, mainly due to practical constraints. …”
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A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…Shared control combines human intelligence with autonomous algorithms, demonstrating potential for enhancing the intricate and dynamic operational capabilities of robots. …”
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Artificial intelligence and machine learning in modern cardiology: Advancements in diagnosis, treatment and patient monitoring by Szymon Kopciał, Dawid Piecuch, Edyta Hańczyk, Karolina Kornatowska, Natalia Pawelec, Weronika Mazur

“…Additionally, AI-driven algorithms support personalized treatment strategies, real-time remote monitoring, and precision-guided coronary interventions, reducing procedural complications. …”
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Recent advances and future technologies in nano-microplastics detection by Ajinkya Nene, Sorour Sadeghzade, Stefano Viaroli, Wenjie Yang, Ucheaga Paul Uchenna, Abhishek Kandwal, Xinghui Liu, Prakash Somani, Massimiliano Galluzzi

“…It highlights promising approaches, supported by practical examples from recent studies, while critically addressing persistent challenges in sampling, characterization, and analysis. …”
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A novel molecular classification system for head and neck squamous cell carcinoma: predicting treatment response and metastatic potential through multi-omics analysis by XinYu Liu, YuJun Liu, XuTengYue Tian, Yue Xi, MiaoMiao Lu, Xin Zou, WanTao Chen

“…The C3 subtype showed enhanced immunotherapy response potential, while C2 exhibited the highest genomic alteration rate (97.06%) and TP53 mutations (80%). …”
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Φ-OTDR disturbance localization of communication optical cable based on moving variance average and spectral subtraction by Wei SHEN, Xin HU, Ze ZHANG, Ling JU, Jian WU, Yi HUANG

“…The results demonstrate that spectral subtraction significantly outperforms the other two algorithms in localization effectiveness, achieving an SNR improvement exceeding 20 dB while maintaining a computational time as low as 0.58 s.…”
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AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects by Soha G. Ahmed, Katrien Verbert, Nazar Zaki, Ashraf Khalil, Hamad Aljassmi, Fady Alnajjar

“…This review examines recent advancements in machine learning algorithms and signal processing for rPPG in driver monitoring. …”
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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

“…TK parameters from the first line and maintenance (TKL1) or after four cycles (TK4) were used to predict PPS and post‐cycle 4 OS (OS4), combined with 12 baseline parameters. While ML algorithms underperformed compared to the Cox model for PPS, a random survival forest was superior for OS prediction using TK4 and surpassed RECIST‐based metrics. …”
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SecFedMDM-1: A Federated Learning-Based Malware Detection Model for Interconnected Cloud Infrastructures by Daniella Mughole Kalimumbalo, Joke A. Badejo, Kennedy O. Okokpujie, Emmanuel Adetiba, Molo Mbasa Joaquim, Nzanzu Vingi Patrick, Gabriel Oyeyemi, Claude Takenga

“…Three distinct deep-learning algorithms were chosen for the models’ training, validation, and testing phases. …”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…The findings demonstrate the effectiveness of combining ML and optimization techniques to enhance biodiesel production efficiency while reducing costs and energy consumption.…”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

“…An empirical investigation using real driving trajectory data from Kunming, China, confirms the ability of our approach to predict potential driving decisions with high accuracy while providing the rationale implicit AV decisions. …”
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Improving resectable gastric cancer prognosis prediction: A machine learning analysis combining clinical features and body composition radiomics by Gianni S.S. Liveraro, Maria E.S. Takahashi, Fabiana Lascala, Luiz R. Lopes, Nelson A. Andreollo, Maria C.S. Mendes, Jun Takahashi, José B.C. Carvalheira

“…Body composition radiomics were integrated with clinicopathological factors using machine learning (ML) algorithms trained for patient outcome prediction. We compared results using Random Forest, Logistic Regression and Boosted Decision Tree algorithms. …”
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Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

“…Ten classification algorithms were applied to the dataset. The accuracy, sensitivity, precision, and feature importance in the machine learning algorithms were assessed and compared to previous studies for evaluation. …”
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FL-DBENet: Double-branch encoder network based on segment anything model for farmland segmentation of large very-high-resolution optical remote sensing images by W. Feng, F. Guan, C. Sun, W. Xu, W. Xu

“…Although deep learning algorithms have been extensively applied to farmland extraction, their performance remains limited due to the scarcity of labeled farmland samples and restricted generalization capabilities. …”
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Visualising fibre path and generating G-code for melt electrowriting of tubular scaffolds using Grasshopper software by Kelly L. O’Neill, Taite McLoughlin, Georgia Van der Linden, Ignacio Lopez Buson, Naomi C. Paxton, Mary Polites, Paul D. Dalton

“…Melt electrowriting (MEW) produces high-resolution, highly porous microfibre scaffolds that are consistently replicable. While typically used to produce planar scaffolds, tubular microfibre structures are increasingly needed for tissue engineering (TE) applications (e.g. vascular TE). …”
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True Leaf Area Index Retrieval Using Terrestrial LiDAR for Broadleaf Trees via Novel Multiinclined-Planes Method by Yuyang Guo, Shihua Li, Hao Tang, Ze He

“…However, results of current TLS-based LAIt retrieval algorithms are highly sensitive to physical parameters such as voxel configuration and gap size. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…Our findings reveal that while traditional machine learning achieved moderate accuracy, it struggled with imbalanced datasets. …”
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Advancements in Cervical Cancer Screening: Enhancing HPV Testing and Triage Strategies for Improved Risk Assessment by Yana Merdzhanova-Gargova, Magdalena Ivanova, Angelina Mollova-Kysebekirova, Anna Mihaylova, Nikoleta Parahuleva-Rogacheva, Ekaterina Uchikova, Mariya Koleva-Ivanova

“…<b>Methods:</b> This study aims to generate detailed statistical data specific to the Bulgarian population, reinforcing the necessity of incorporating updated European methodologies and algorithms for the prophylaxis and prevention of cervical carcinoma. …”
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A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…Other optimization algorithms including ARO, TLBO, DE and SSA are used for comparative analysis purposes. …”
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The relationship between epigenetic biomarkers and the risk of diabetes and cancer: a machine learning modeling approach by Shiqi Zhang, Shiqi Zhang, Jianan Jin, Benfeng Xu, Qi Zheng, Haibo Mou

“…Nine machine learning algorithms were used to build models: AdaBoost, GBM, KNN, lightGBM, MLP, RF, SVM, XGBoost, and logistics. …”
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