Mammography reporting dataset with BI-RADS system for natural language processing applications: Addressing public data gaps in SpanishZENODO by José Luis Vázquez Noguera, Alejandro Torres-Hurtado, Helena Gómez-Adorno, Julio César Mello-Román, Enrique Javier Fleitas-Alvarez, Federico Fernando Espinola Schulze, Miguel Garcia-Torres, Carlos Domingo Méndez Gaona, Pedro Esteban Gardel Sotomayor, Silvia Vázquez Noguera, Norma Elizabeth Zaracho Amarilla, Oxades Wilfrido Gamarra Esquivel

“…It provides real-world data for developing and testing NLP algorithms and machine learning models, specifically for automating BI-RADS classification and analyzing mammography reports.…”
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Self-Stabilization of Grid-Connected Inverters by Means of an Impedance-Based Adaptive Controller by Joel Filipe Guerreiro, Tiago Davi Curi Busarello, Hildo Guillardi, Igor Alves Maronni, Jose De A. Olimpio Filho, Helmo K. Morales Paredes, Jose A. Pomilio

“…<italic>LCL</italic>-type ac filters and resonant-based controllers also pose challenges to the stability of the operation. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Therefore, CNN is used as the fault prediction also. The model is implemented using Python programming language and demonstrated its effectiveness on test cases. …”
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Machine Learning-Based Alfalfa Height Estimation Using Sentinel-2 Multispectral Imagery by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Rami Albasha, Md Saifuzzaman, Maxime Leduc

“…Three machine learning algorithms were employed to estimate plant height from satellite images: random forest (RF), support vector regression (SVR), and extreme gradient boosting (XGB). …”
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Playing hide and seek with primates: A comparative study of Theory of Mind by Aurore San‑Galli, Marie Devaine, Cinzia Trapanese, Shelly Masi, Sébastien Bouret, Jean Daunizeau

“…In fact, the location of the food was chosen by learning algorithms, some of which endowed with artificial ToM. …”
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Comparison of methods for resolving the contributions of local emissions to measured concentrations by T. D. Edwards, Y. K. Wong, C.-H. Jeong, J. M. Wang, Y. Su, G. J. Evans

“…A variety of published methods exist to complete this task, like placing measurements upwind the emitter, employing a distant background measurement station, or algorithmic methods that extract a background from the time series of measured concentrations (e.g. wavelet decomposition). …”
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Diagnostics-linked Antimicrobial Surveillance: A Route to Patient-Centred Microbiology Diagnostics? by Dr Alex Howard, Dr Charlotte Brookfield, Dr Conor Rosato, Dr Anoop Velluva, Dr Alessandro Gerada, Professor William Hope

“…In this study we trialled a microbiology diagnostics-linked antimicrobial surveillance (DLAS) algorithmic approach on real-world urine antimicrobial susceptibility testing and antimicrobial prescribing data. …”
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Predicting Resistance and Survival of HCC Patients Post-HAIC: Based on Shapley Additive exPlanations and Machine Learning by Yao F, Miao J, Quan B, Li J, Tang B, Lu S, Yin X

“…Random Forest had the best performance among the seven ML algorithms (AUC=0.935 for training, AUC=0.876 for validation). …”
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The new era of artificial intelligence in neuroradiology: current research and promising tools by Fabíola Bezerra de Carvalho Macruz, Ana Luiza Mandetta Pettengil Dias, Celi Santos Andrade, Mariana Penteado Nucci, Carolina de Medeiros Rimkus, Leandro Tavares Lucato, Antônio José da Rocha, Felipe Campos Kitamura

“…In light of this, in this article we survey the existing literature on the application of AI-based techniques in neuroradiology, focusing on conditions such as vascular diseases, epilepsy, and demyelinating and neurodegenerative conditions. We also introduce some of the algorithms behind the applications, briefly discuss a few of the challenges of generalization in the use of AI models in neuroradiology, and skate over the most relevant commercially available solutions adopted in clinical practice. …”
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Moth walls: shedding light on moth biodiversity by Joseph J. Bowden, Avalon Owens, Kayla Brown, Robert W. Harding, Marianne Graversen, Maxim Larrivée, Kent McFarland, Tyler A. Miller, Jamie Warren, Jodi O. Young

“…Its members contribute to important ecosystem services such as pollination and herbivory while also serving as principal food for many other animals. …”
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Multi-photon neuron embedded bionic skin for high-precision complex texture and object reconstruction perception research by Hongyu Zhou, Chao Zhang, Hengchang Nong, Junjie Weng, Dongying Wang, Yang Yu, Jianfa Zhang, Chaofan Zhang, Jinran Yu, Zhaojian Zhang, Huan Chen, Zhenrong Zhang, Junbo Yang

“…It also allows for the classification of fabrics with different surface textures with 98.5% accuracy and Braille patterns with 99% accuracy. …”
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Ethics, Animal Welfare, and Artificial Intelligence in Livestock: A Bibliometric Review by Taize Calvacante Santana, Cristiane Guiselini, Héliton Pandorfi, Ricardo Brauer Vigoderis, José Antônio Delfino Barbosa Filho, Rodrigo Gabriel Ferreira Soares, Maria de Fátima Araújo, Nicoly Farias Gomes, Leandro Dias de Lima, Paulo César da Silva Santos

“…Keyword co-occurrence and bibliographic coupling analyses revealed the formation of four main thematic clusters, covering technical applications in precision livestock farming as well as reflections on governance, animal welfare, and algorithmic justice. The most influential authors, high-impact journals, and leading countries in the field were also identified. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…This scheme is not only applicable to VCS, but can also provide reference for other fields involving credit prediction and incentive mechanisms.…”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…BackgroundThe rapid advancement of technology has brought numerous benefits to public health but has also contributed to a rise in sedentary lifestyles, linked to various health issues. …”
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First study of the RuPatient health information system with optical character recognition of medical records based on machine learning by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, D. N. Samochatov, E. V. Koshkina, E. V. Bushueva, O. M. Drapkina

“…RuPatient health information system (HIS) is a computer program consisting of a doctor-patient web user interface, which includes algorithms for recognizing medical record text and entering it into the corresponding fields of the system.Aim. …”
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Digital Academic Leadership in Higher Education Institutions: A Bibliometric Review Based on CiteSpace by Olaniyi Joshua Olabiyi, Carl Jansen van Vuuren, Marieta Du Plessis, Yujie Xue, Chang Zhu

“…This was the result of a multi-step refinement process using CiteSpace’s default thresholds and clustering algorithms to detect the most influential nodes based on centrality, citation burst, and network clustering. …”
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RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review by Md Nasim Reza, Kyu-Ho Lee, Eliezel Habineza, Samsuzzaman, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…Machine vision and image processing algorithms enable for the real-time detection of subtle changes in pig appearance and behavior that may signify potential health issues. …”
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Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

“…ABSTRACT The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…Potential future research directions are also identified. This review presents an overview of multimodal machine learning (MMML) in radiology, a field at the cutting edge of integrating artificial intelligence into medical imaging. …”
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The key genes ME1 and ALDH3A1 involved in glycolysis regulate the lactate pathway and mediate COPD related immune dysregulation by Wenli XIE, Guang ZHOU, Zhitao JING, Shilin QIU

“…Subsequently, key genes involved in glycolysis were identified using the LASSO and SVM-RFE algorithms. After subtyping, GSEA analysis was conducted. …”
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