Diseases with major salivary glands enlargement and orbits, nose and paranasal sinuses lesions in the practice of a rheumatologist by E. V. Sokol, A. V. Torgashina, B. D. Chaltsev, Yu. I. Khvan, O. A. Golovina

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Application of statistical methods for predicting udp-flood attacks by M. V. Tumbinskaya, V. V. Volkov, B. G. Zagidullin

“…In order to improve the level of protection against DDoS attacks, further research should be aimed at developing methods for combating UDP-flood attacks and algorithms increasing the information security of web resources, as well as implementing measures to improve the security of web-based resources.…”
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Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. …”
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Species delimitation and microalgal cryptic diversity analysis of the genus Micractinium (Chlorophyta) by E. S. Krivina, A. D. Temraleeva, Yu. S. Bukin

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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…By leveraging advanced algorithms and machine learning techniques, the research aims to streamline the allocation of tasks and responsibilities among various stakeholders, including farmers, agronomists, technicians, and AI systems. …”
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Novel candidate genes may be possible predisposing factors revealed by whole exome sequencing in familial esophageal squamous cell carcinoma by Narjes Forouzanfar, Ancha Baranova, Saman Milanizadeh, Alireza Heravi-Moussavi, Amir Jebelli, Mohammad Reza Abbaszadegan

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La Teoría del andamiaje como herramienta de construcción del pensamiento matemático by Cesar Orlando Vargas Mantilla, Sonia Maritza Mendoza Lizcano, Wlamyr Palacios Alvarado

“…This research responded to the needs expressed in various academic spaces, which are publicly visible, regarding the poor performance in national and international tests in aspects of mathematical knowledge. …”
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The Prediction of Venous Thromboembolism Using Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Systematic Review by Davood Dalil, MD, Sina Esmaeili, Ehsan Safaee, Sajad Asgari, Nooshin Kejani, MD

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Magnetic resonance imaging relevance in diagnosis and prognosis of early postoperative period following pancreatic cancer surgical treatment by E. N. Kolesnikov, D. Ya. Iozefi, O. I. Kit, A. Yu. Maksimov

“…Improvement of the prognostic outcomes for the pancreatic fistula development in surgical treatment for pancreatic cancer by implementation of new diagnostic algorithms for magnetic resonance imaging (MRI) assessment of supposed pancreatic stump.Materials and methods. …”
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Analysis of prognostic factors and nomogram construction for postoperative survival of triple-negative breast cancer by Chenxi Wang, Xiangqian Zhao, Dawei Wang, Jinyun Wu, Jizhen Lin, Weiwei Huang, Yangkun Shen, Qi Chen

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Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism by Qiang Wang, Zhihang Yu, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Zhiqiang Zou, Weiming Huang, Christophe Claramunt

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Harmonizing Landsat-8 OLI and Sentinel-2 MSI: an assessment of surface reflectance and vegetation index consistency by Jiaqi Zhang, Xiaocheng Zhou, Xueping Liu, Xiaoqin Wang, Guojin He, Youshui Zhang

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Optimized deep learning models for stress-based stroke prediction from EEG signals by Sivasankaran Pichandi, Gomathy Balasubramanian, Venkatesh Chakrapani, J. Samuel Manoharan

“…These responses are linked to an elevated risk of cardiovascular diseases, which, in turn, can heighten the risk of stroke. The proposed research aims to classify stress-induced emotions and predict stroke risk using advanced deep learning algorithms. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…The study also discusses key applications in drug design and materials science, demonstrating how chemoinformatics drives efficiency and sustainability in research. Additionally, it outlines future challenges and opportunities, emphasizing the need for improved algorithms, data standardization, and interdisciplinary collaboration. …”
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Emerging trends and knowledge networks in pan-cancer sorafenib resistance: a 20-year bibliometric investigation by Qiong Zhou, Rui Wang

“…Future research priorities should include biomarker-driven clinical trials, the development of nanoparticle delivery systems, and the clinical translation of combination therapy strategies. …”
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Image dataset: UAV images and ground data of one ‘Bingo’ mandarin and two ‘Valencia’ orange rootstock trials conducted in FloridaAg Data CommonsAg Data Commons by Randall P. Niedz, Kim D. Bowman

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Future impacts of artificial intelligence technologies in graphic design by Hussein Nasser Ibrahim Saleh Al-Dulaimi

“…Thanks to advanced algorithms and software, it has become possible to create innovative and attractive designs faster and easier than before. …”
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Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis by Faisal Abdulaziz Almisned, Natacha Usanase, Dilber Uzun Ozsahin, Ilker Ozsahin

“…Recently, a potential approach that has attracted significant attention is using machine learning in clinical decision-making. This research aims to analyze six machine learning algorithms, and an ensemble voting classifier, develop hybrid models for the early detection of pancreatic cancer based on several clinical characteristics and interpret their performance with Shapley Additive Explanations (SHAP). …”
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Evaluating Recycling Initiatives for Landfill Diversion in Developing Economies Using Integrated Machine Learning Techniques by Muyiwa Lawrence Adedara, Ridwan Taiwo, Olusola Olaitan Ayeleru, Hans-Rudolf Bork

“…It evaluates the recycling diversion rate (RDR) of household recyclables (HSRs) across local government areas using field surveys and population data. Machine learning algorithms (logistic regression, random forest, XGBoost, and CatBoost) refined with Bayesian optimisation were employed to predict household recycling motivation. …”
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The current state of the problem of tick-borne encephalitis in Russia and the world by N. M. Kolyasnikova, A. A. Ishmukhametov, V. G. Akimkin

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