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Academic Articles & Research Papers
Showing 20 of 2,780 academic articles
Sebastian Raschka, Joshua M. Patterson, Corey Nolet • Information
(2020)
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the...
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DOI: https://doi.org/10.3390/info11040193
Yu‐Chen Lo, Stefano Rensi, Wen Torng, Russ Biagio Altman • Drug Discovery Today
(2018)
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learn...
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DOI: https://doi.org/10.1016/j.drudis.2018.05.010
PMC: 6078794
Zhao D, Qin D, Yin L, Yang Q • Pharmacogenomics and Personalized Medicine
(2023)
Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...
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Open Access (DOAJ)
Walaa Mohamed Najeb • Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Adāb - Ǧāmiʿaẗ Asyūṭ
(2026)
Technology has undergone rapid advancements, significantly impacting various sectors, with the tourism industry emerging as one of the most benefited. This research examines several key aspects, including: An overview of Cairo and Dubai as ...
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Open Access (DOAJ)
DOI: 10.21608/aakj.2025.429364.2248
Jongho Lee, Jiuk Shin, Jaewook Lee, Chorong Park et al. • Applied Sciences
(2023)
Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage...
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Open Access (DOAJ)
DOI: 10.3390/app132111866
Michael I. Jordan, Tom M. Mitchell • Science
(2015)
Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and a...
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DOI: https://doi.org/10.1126/science.aaa8415
Mario D. Molina, Filiz Garip • Annual Review of Sociology
(2019)
Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...
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Open Access
DOI: https://doi.org/10.1146/annurev-soc-073117-041106
Atılım Güneş Baydin, Barak A. Pearlmutter, Alexey Radul, Jeffrey Mark Siskind • Maynooth University ePrints and eTheses Archive (Maynooth University)
(2015)
Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Automatic differentiation (AD) is a technique for calculating derivatives of numeric functions expressed as computer programs efficiently and acc...
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Open Access
Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos • Annual Review of Fluid Mechanics
(2019)
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...
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Open Access
DOI: https://doi.org/10.1146/annurev-fluid-010719-060214
Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida, Vandecia Rejane Monteiro Fernandes et al. • Data in Brief
(2025)
Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...
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Open Access (DOAJ)
DOI: 10.1016/j.dib.2025.111823
Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science
(2025)
This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...
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Open Access (DOAJ)
DOI: 10.30919/es1972
Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making
(2024)
Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...
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Open Access (DOAJ)
DOI: 10.1186/s12911-024-02652-7
Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies
(2026)
A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...
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Open Access (DOAJ)
DOI: 10.3390/technologies14030189
Kevin P. Murphy (2012)
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...
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Jing Wei, Xuan Chu, Xiangyu Sun, Kun Xu et al. • InfoMat
(2019)
Abstract Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to the...
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DOI: https://doi.org/10.1002/inf2.12028
Yalın Baştanlar, Mustafa Özuysal • Methods in molecular biology
(2013)
The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity ...
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Open Access
DOI: https://doi.org/10.1007/978-1-62703-748-8_7
Stephen Marsland • Chapman & Hall/CRC eBooks
(2014)
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing wo...
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DOI: https://doi.org/10.1201/b17476
S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks
(2011)
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...
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DOI: https://doi.org/10.7551/mitpress/8996.001.0001
Yong Wang, Hongwen He, Yuankai Wu, Pei Wang et al. • Engineering
(2025)
An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasin...
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Open Access (DOAJ)
DOI: 10.1016/j.eng.2024.10.021
Ryunosuke Noda, Daisuke Ichikawa, Yugo Shibagaki • Scientific Reports
(2024)
Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-73898-4