Artificial Intelligence Models Accuracy for Odontogenic Keratocyst Detection From Panoramic View Radiographs: A Systematic Review and Meta‐Analysis by Reyhaneh Shoorgashti, Mohadeseh Alimohammadi, Sana Baghizadeh, Bahareh Radmard, Hooman Ebrahimi, Simin Lesan

“…While deep learning algorithms in AI have shown promise in improving diagnostic accuracy for OKCs, their performance across studies is still unclear. …”
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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. …”
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Analysis of the Current State of Digitalization İmplementation in the Banking System of Azerbaijan by K. N. Atayev

“…Recent indexes confirm that the integration of mobile technologies, biometric identification systems, artificial intelligence algorithms, and fintech innovations has served as a significant catalyst for the transformation of this sector. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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Correspondence distribution over a network in designing public urban passenger transportation tasks by A. I. Fadeev, A. M. Iliankov, V. V. Ukaderov

“…The formation acceptable routes on the transport network can be carried out by means of the algorithms developed, for example, in the framework of solving TNDP and TNDFSP tasks. …”
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Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

“…The Random Forest (RF), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), and Extreme Gradient Boosting (XG-Boost) were identified as the mostly used ML algorithms. Most often applied deep learning techniques include long short-term memory (LSTM) and convolutional neural networks (CNNs). …”
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Leveraging AI to explore structural contexts of post-translational modifications in drug binding by Kirill E. Medvedev, R. Dustin Schaeffer, Nick V. Grishin

“…Recent advancements in computational power and artificial intelligence, particularly in deep learning algorithms and protein structure prediction tools like AlphaFold3, have opened new possibilities for exploring the structural context of interactions between PTMs and drugs. …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…Conclusions The measures identified are not only feasible from real-world PHC records but also give some useful metrics about how well current HL-management is going and what future actions are needed.…”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…This contribution strengthens the robustness and adaptability of DRL agents by enabling better generalization of learned policies compared with their baseline counterparts, while also significantly improving trajectory tracking performance. …”
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Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…This explorative study aims to uncover the potential of random forest machine learning algorithms as survival models within the biomedical context of T1D. …”
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Using large language models for enhanced fraud analysis and detection in blockchain based health insurance claims by Ruba Islayem, Senay Gebreab, Walaa AlKhader, Ahmad Musamih, Khaled Salah, Raja Jayaraman, Muhammad Khurram Khan

“…In addition, an LLM-powered chatbot also allows insurance providers to interact with the system in natural language for claim inquiries, explanations, and summaries. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…Using this approach, the Saronikos Gulf was enriched with five more habitat types than visualised in the EMODnet portal, which also filled habitat gaps in areas where no data existed. …”
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HUMAN RIGHTS: PHILOSOPHICAL AND LEGAL ANALYSIS by ALBOV A.P.

“…Thus, the issue of observance of these rights, as well as their restrictions, is not only an internal problem of individual political communities, but also a problem of the entire civilized world. The main purpose of the article is to identify the historical and logical common ground in the dialogue of various Western scientific schools on the basic concepts of human rights. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…Intra- and inter-rater variation is frequently imposed on by technicians who are underqualified and unexperienced. Alternatively, algorithms could support local employees in tracking disease transmission and quick action, especially in Thailand where this cattle disease is common. …”
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Machine learning-based predictive modeling of angina pectoris in an elderly community-dwelling population: Results from the PoCOsteo study. by Shahrokh Mousavi, Zahrasadat Jalalian, Sima Afrashteh, Akram Farhadi, Iraj Nabipour, Bagher Larijani

“…We aimed to develop machine learning-based models using multiple algorithms to predict and identify the predictors of angina pectoris in an elderly community-dwelling population.…”
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Natural Language Processing and Machine Learning Techniques for Analyzing Conversations About Nutritional Yeasts in the United States and France: Retrospective Social Media Listeni... by Jean-François Jeanne, Joelle Malaab, Antoine Vanhove, Florian Mourey, Manissa Talmatkadi, Stéphane Schück

“…Data cleaning and filtering were done using natural language processing methods and specific algorithms. Biterm topic modeling was applied to identify the most frequently discussed topics. …”
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Hibridación de sistemas borrosos para el modelado y control by José Manuel Andújar, Antonio Javier Barragán

“…Palabras clave: Algoritmos bioinspirados, control borroso, control inteligente, modelado borroso, redes neuronales, sistemas borrosos, sistemas híbridos, Keywords: Bioinspired algorithms fuzzy control fuzzy modeling fuzzy systems hybrid systems intelligent control neuronal networks…”
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Cropping and Transformation Features of Non-Grain Cropland in Mainland China and Policy Implications by Yizhu Liu, Ge Shen, Tingting He

“…Remote sensing is regarded as the most effective and accurate method for this purpose, but existing studies have mainly focused on algorithms operating at the local scale or exploring grain-producing capability from the perspective of agricultural space. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…Automatic speech recognition (ASR) and speech enhancement are essential tools in modern life, aiding not only in machine interaction but also in supporting individuals with hearing impairments. …”
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Identification of neoantigen epitopes in cervical cancer by multi-omics analysis by Jing Yuan, Na Xu, Xueqi Gong, Jihui Ai, Kezhen Li, Yingyan Han

“…We also stimulated PBMC from patients with the corresponding HLA type with the synthesized peptides using an ELISpot assay. …”
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