Neurons throughout the brain embed robust signatures of their anatomical location into spike trains by Gemechu Bekele Tolossa, Aidan M Schneider, Eva Dyer, Keith B Hengen

“…However, whether individual neurons also embed information about their own anatomical location within their spike patterns remains largely unexplored. Here, we show that machine learning models can predict a neuron’s anatomical location across multiple brain regions and structures based solely on its spiking activity. …”
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Characterization of braided river reservoir architecture based on seismic attribute stacking ensemble learning: A case study of the C-2 oilfield in the Bohai Bay Basin by ZHANG Zhang, MENG Peng, YANG Wei, ZHANG Xiaolong, HUANG Qi, WANG Haoran

“…This method can serve as a reference for the detailed characterization of fluvial-facies reservoir configurations during the middle and late development stages of offshore oilfields with sparse well patterns.…”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Prospects for the use of artificial neural networks for problem solving in clinical transplantation by R. M. Kurabekova, A. A. Belchenkov, O. P. Shevchenko

“…Machine learning technologies are based on the concept of a machine that mimics human intelligence and and makes it possible to identify patterns that are inaccessible to traditional methods. …”
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Implementation of a hierarchical cluster model to analyze wind and solar availability in the department of Antioquia, Colombia by Alejandro Restrepo Román, Didier J. Villegas, Carolina Rodriguez, Adrián Cogollo, Iván D. Bedoya, Andres A. Amell Arrieta

“…This research presents a systematic spatiotemporal assessment of solar radiation and wind speed patterns throughout the Department of Antioquia, Colombia, employing advanced machine learning methodologies to evaluate renewable resource potential. …”
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A Dynamic Monitoring Framework for Spring Low-Temperature Disasters Affecting Winter Wheat: Exploring Environmental Coercion and Mitigation Mechanisms by Meixuan Li, Zhiguo Huo, Qianchuan Mi, Lei Zhang, Jianying Yang, Fengyin Zhang, Rui Kong, Yi Wang, Yuxin Huo

“…Subsequently, using the XGBoost algorithm to analyze the differences between spring frost and cold damage patterns, a model for identifying types of spring LTDs was developed. …”
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Data mining techniques for the study of online learning from an extended approach by José Manuel Sánchez-Sordo

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Artificial intelligence for the understanding of electrolyte chemistry and electrode interface in lithium battery by Chen Yawei, Liu Yue, He Zixu, Xu Liang, Yu Peiping, Sun Qintao, Li Wanxia, Jie Yulin, Cao Ruiguo, Cheng Tao, Jiao Shuhong

“…Recognizing the critical role of electrolyte chemistry and electrode interfaces in the performance and safety of lithium batteries, along with the urgent need for more sophisticated methods of analysis, this comprehensive review underscores the promise of machine learning (ML) models in this research field. …”
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Learning Radio Environments by Differentiable Ray Tracing by Jakob Hoydis, Faycal Ait Aoudia, Sebastian Cammerer, Florian Euchner, Merlin Nimier-David, Stephan Ten Brink, Alexander Keller

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Artificial Intelligence: The Latest Advances in the Diagnosis of Bladder Cancer by Satyendra Singh, Ram Mohan Shukla

“…AI systems can analyze vast amounts of data from various sources, such as medical imaging, genomic data, and electronic health records, enabling the identification of subtle patterns and biomarkers that may indicate the presence of bladder cancer. …”
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A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

“…These intervals capture key patterns, enhancing adaptability and insight. To improve robustness, we incorporate outranking measures, which reduce the impact of noise and uncertainty through pairwise comparisons of alternatives across features. …”
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Investigating the Temporal Sensitivity of Upper Ocean Salinity to Global Water Cycle Changes With Unsupervised Learning by Chao Liu, Xinfeng Liang, Rui M. Ponte

“…Abstract The response of ocean salinity to surface freshwater fluxes exhibits complex spatial and temporal patterns, making it challenging to pinpoint where and when freshwater flux dominates salinity variability. …”
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CINNAMON: A hybrid approach to change point detection and parameter estimation in single-particle tracking data by Jakub Malinowski, Marcin Kostrzewa, Michał Balcerek, Weronika Tomczuk, Janusz Szwabiński

“…Change point detection has become an important part of the analysis of the single-particle tracking (SPT) data, as it allows one to identify moments, in which the motion patterns of observed particles undergo significant changes. …”
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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…The method identifies linear laws that capture shared patterns within a reference class, enabling compact and verifiable representations of time series data. …”
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Research on noise prediction methods for sound barriers based on the integration of conditional generative adversarial networks and numerical methods by Qian Hu, Ziyu Cui, Hongxue Liu, Senhao Zhong

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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…The AI-powered systems can easily identify the specific patterns within the electrochemical signals that otherwise remain undetectable by traditional methods. …”
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Intelligent visibility forecasting at airports: a systematic review by Décio Alves, Margarida Belo-Pereira, Fábio Mendonça, Fernando Morgado-Dias

“…This review synthesizes findings on data-driven solutions, including machine learning and deep learning, that harness large datasets to reveal hidden patterns, offering better performance and adaptability. …”
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A Deep Learning-Based Prediction and Forecasting of Tomato Prices for the Cape Town Fresh Produce Market: A Model Comparative Analysis by Emmanuel Ekene Okere, Vipin Balyan

“…Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. …”
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Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement by Frédéric Marty, Thierry Warin

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Implementation of Generative Artificial Intelligence in Sociological Research by V. E. Drach, Yu. V. Torkunova

“…The results of the study demonstrate that the use of GAI allows for significantly accelerating the data processing process and enhancing the quality of the data. New patterns and trends in sociological research have been identified, enabling researchers to draw more accurate and justified conclusions. …”
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