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Showing 20 of 23,220 academic articles
Matthias S. Treder • Frontiers in Neuroscience
(2020)
MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native implementations of a range of classifiers and regression models, using modern optimization algorithms. High-level functions allow for the multivaria...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnins.2020.00289
Zella King, Joseph Farrington, Martin Utley, Enoch Kung et al. • npj Digital Medicine
(2022)
Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabi...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41746-022-00649-y
Rasmus Dovnborg Frederiksen, Grzegorz Radzki, Grzegorz Bocewicz, Peter Nielsen et al. • Applied Sciences
(2026)
This paper investigates the relationship between the benefits achieved by predictive maintenance implementation and the related costs incurred intentionally or not. Specifically, we seek to establish an evaluation method for predictive main...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16178708
Alberto Gil-Maciá, J. Enrique Sierra-García, Matilde Santos • Machine Learning with Applications
(2026)
Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2026.100919
Joseph A. Cruz, David Scott Wishart • Cancer Informatics
(2006)
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.1177/117693510600200030
PMC: 2675494
Shijun Wang, Ronald M. Summers • Medical Image Analysis
(2012)
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Open Access
DOI: https://doi.org/10.1016/j.media.2012.02.005
PMC: 3372692
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
OPENALEX
DOI: https://doi.org/10.1145/3494672
Oswald Campesato • De Gruyter eBooks
(2020)
This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fun...
OPENALEX
DOI: https://doi.org/10.1515/9781683924937
Flávio Barboza, Herbert Kimura, Edward I. Altman • Expert Systems with Applications
(2017)
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DOI: https://doi.org/10.1016/j.eswa.2017.04.006
D. E. Goldberg (1989)
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Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar • The MIT Press eBooks
(2018)
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference fo...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.7551/mitpress/10290.001.0001
Michael Paluszek, Stephanie J. Thomas • Apress eBooks
(2016)
This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It prov...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-2250-8
Qifang Bi, Katherine E Goodman, Joshua Kaminsky, Justin Lessler • American Journal of Epidemiology
(2019)
Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well...
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DOI: https://doi.org/10.1093/aje/kwz189
Claire Nédellec, Céline Rouveirol • Lecture notes in computer science
(1998)
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DOI: https://doi.org/10.1007/bfb0026664
Tim Mueller, Aaron Gilad Kusne, Rampi Ramprasad • Reviews in computational chemistry
(2016)
This chapter addresses the role that data-driven approaches, especially machine learning methods, are expected to play in materials research in the immediate future. Machine learning, an important part of artificial intelligence, has made m...
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DOI: https://doi.org/10.1002/9781119148739.ch4
Taiwo Oladipupo Ayodele • InTech eBooks
(2010)
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cc-by-nc-sa
DOI: https://doi.org/10.5772/9394
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications
(2022)
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...
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DOI: https://doi.org/10.1038/s41467-022-27980-y
PMC: 8828720
Haaf D, McGlade M, Nghiem AA, Vu DT et al. • Environmental science & technology
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1021/acs.est.6c07700
PMC: PMC13738782
Ortiz R, Dwivedi SL, Pelikan A, Goldman IL • TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1007/s00122-026-05426-z
PMC: PMC13736410