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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, ...
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cc-by-nc
DOI: https://doi.org/10.1177/117693510600200030
PMC: 2675494
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...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.gsf.2015.07.003
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
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...
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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
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
Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour • ICT Express
(2026)
The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.icte.2026.01.005
Hilal M. El Misilmani, Tarek Naous • International Conference on High Performance Computing & Simulation (HPCS)
(2019)
With the growth and wide variety of available data, advanced processing, and affordable data storage, machine learning is witnessing great attention in finding optimized solutions in various fields. Machine learning techniques are currently...
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DOI: https://doi.org/10.1109/hpcs48598.2019.9188224
Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology
(2007)
The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...
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public-domain
DOI: https://doi.org/10.1371/journal.pcbi.0030116
PMC: 1904382
Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich et al. • eNeuro
(2020)
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve deco...
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DOI: https://doi.org/10.1523/eneuro.0506-19.2020
PMC: 7470933
Rafael A. Irizarry • Chapman & Hall/CRC eBooks
(2019)
The machine learning approach is to train an algorithm using a dataset for which the people do know the outcome, and then apply this algorithm in the future to make a prediction when they don't know the outcome. In this chapter, the authors...
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DOI: https://doi.org/10.1201/9780429341830-27
Leavitt H, Thomas A, Nelson JA • Ecological applications : a publication of the Ecological Society of America
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1002/eap.70318
PMC: PMC13735485
Eslam Abdelkreem, Sherif Hussein, Ashraf Tammam • Scientific Reports
(2026)
Abstract Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of information. Consequently, many applications that can enhance passengers’ safety a...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-39867-9
Bardia Abbasi, Daniel M. Goldenholz • Epilepsia
(2019)
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...
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Open Access
DOI: https://doi.org/10.1111/epi.16333
PMC: 9897263
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
Naga Ramesh Palakurti, Nageswararao Kanchepu • Advances in systems analysis, software engineering, and high performance computing book series
(2024)
This chapter delves into the core principles of machine learning, offering practical insights for effective data processing. From foundational concepts to advanced techniques, the narrative unfolds as a comprehensive guide for harnessing th...
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DOI: https://doi.org/10.4018/979-8-3693-2909-2.ch002
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 ...
DOAJ
Open Access (DOAJ)
DOI: 10.21608/aakj.2025.429364.2248
Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics
(2014)
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....
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DOI: https://doi.org/10.3389/fninf.2014.00014
PMC: 3930868
Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks
(2014)
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...
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DOI: https://doi.org/10.1017/cbo9781107298019
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
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DOI: https://doi.org/10.1017/cbo9780511804779