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Academic Articles & Research Papers
Showing 20 of 648 academic articles
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause, Lily H. Peng • JAMA
(2019)
In recent years, many new clinical diagnostic tools have been developed using complicated machine learning methods. Irrespective of how a diagnostic tool is derived, it must be evaluated using a 3-step process of deriving, validating, and e...
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DOI: https://doi.org/10.1001/jama.2019.16489
Philomena Schlexer, Kirsten T. Winther, José Antonio Garrido Torres, Verena Streibel et al. • ChemCatChem
(2019)
Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the developme...
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DOI: https://doi.org/10.1002/cctc.201900595
Geoffrey Holmes, A. Donkin, Ian H. Witten • Australian and New Zealand Intelligent Information Systems Conference (ANZIIS)
(2002)
WEKA is a workbench for machine learning that is intended to aid in the application of machine learning techniques to a variety of real-world problems, in particular, those arising from agricultural and horticultural domains. Unlike other m...
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DOI: https://doi.org/10.1109/anziis.1994.396988
Dipanjan Sarkar, Raghav Bali, Tushar Sharma • Apress eBooks
(2017)
This book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, desi...
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DOI: https://doi.org/10.1007/978-1-4842-3207-1
Maximilian Pichler, Florian Hartig • Methods in Ecology and Evolution
(2023)
Abstract The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI) has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML and DL algorithms are often perceived as opa...
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DOI: https://doi.org/10.1111/2041-210x.14061
K. W. DeGregory, Patrick K. Kuiper, Thomas DeSilvio, James D. Pleuss et al. • Obesity Reviews
(2018)
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...
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Open Access
DOI: https://doi.org/10.1111/obr.12667
PMC: 8176949
Parliamentary Office of Science and Technology, Lorna Christie (2020)
Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that ...
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Open Access
DOI: https://doi.org/10.58248/pn633
Keywan Christian Rasekhschaffe, Robert C. Jones • Financial Analysts Journal
(2019)
Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can un...
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DOI: https://doi.org/10.1080/0015198x.2019.1596678
Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong • Cambridge University Press eBooks
(2020)
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in d...
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DOI: https://doi.org/10.1017/9781108679930
Chia-Chin Chuang, Zheng-Wei Lin Chi, Tzu-Chien Kuo, Che-Jui Chang et al. • Machines
(2026)
Structural aging and environmental changes associated with long-term operation can substantially modify the thermal behavior of machine tools, diminishing the accuracy of existing thermal compensation models. Traditional neural network appr...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/machines14030309
Vijaya B. Kolachalama, Priya S. Garg • npj Digital Medicine
(2018)
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and othe...
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DOI: https://doi.org/10.1038/s41746-018-0061-1
PMC: 6550167
• The MIT Press eBooks
(2012)
Foundations of Machine LearningSoon we will embark on a theoretical study of AdaBoost in order to understand its properties, particularly its ability as a learning algorithm to generalize, that is, to make accurate predictions on data not s...
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cc-by-nc-nd
DOI: https://doi.org/10.7551/mitpress/8291.003.0006
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...
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DOI: https://doi.org/10.7551/mitpress/10290.001.0001
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
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
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
M.Á. Luján, R. Young-Morrison, V. Kashtelyan, G. Loewinger et al. • Cell Reports
(2026)
Summary: Quickly adapting behavior to changing environments is key for survival. Brain dopamine signals reinforce actions that procure rewards and avoid adverse outcomes. However, the molecular mechanisms within the circuits that actuate th...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.celrep.2026.117298
Edoardo Bizzotto, Guido Zampieri, Laura Treu, Pasquale Filannino et al. • Computational and Structural Biotechnology Journal
(2024)
Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.csbj.2024.05.040
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
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