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Showing 20 of 2,633 academic articles
Mohamad Kazemi, Atefeh Jafarpoor, Youssef Ahmadi, Raoof Mostafazadeh • Scientific Reports
(2026)
Abstract The expansion of human activities and environmental changes in coastal desert and semi-desert ecosystems significantly impact habitat quality. This study used remote sensing data on the Google Earth Engine (GEE) platform to generat...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-47305-z
Jennifer K. Briggs, J. N. Stroh, Soojin Park, Brandon Foreman et al. • npj Digital Medicine
(2026)
Abstract Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure and physiological mechanisms collectively referred to as cerebral vascular regulation (CVR). Direct measurement of cerebral blood fl...
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Open Access (DOAJ)
DOI: 10.1038/s41746-026-02600-x
Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access
(2025)
This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3567410
Cheng-Hong Yang, Chih-Hsien Wu, Kuei-Hau Luo, Huang-Chih Chang et al. • Ecotoxicology and Environmental Safety
(2024)
Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This st...
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Open Access (DOAJ)
DOI: 10.1016/j.ecoenv.2024.116885
• 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
Nora Alhazmi, Rana Almazroa, Muhannad Alshehri, Saad Bin Shabib et al. • Journal of Orthodontic Science
(2026)
OBJECTIVES:
This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...
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Open Access (DOAJ)
DOI: 10.4103/jos.jos_111_25
Jiaoling Qin, Jiaoling Qin, Sunzhe Li, Sunzhe Li et al. • Frontiers in Marine Science
(2023)
Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...
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Open Access (DOAJ)
DOI: 10.3389/fmars.2022.1113387
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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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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DOI: https://doi.org/10.1016/j.gsf.2015.07.003
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
Tao Song, Jiarong Wang, Danya Xu, Wei Wei et al. • Journal of Marine Science and Engineering
(2021)
Physical oceanography models rely heavily on grid discretization. It is known that unstructured grids perform well in dealing with boundary fitting problems in complex nearshore regions. However, it is time-consuming to find a set of unstru...
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Open Access (DOAJ)
DOI: 10.3390/jmse9121398
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
Noémie Letellier, Caitlin G. Jones-Ngo, Michael W. Cheung, Rosana Aguilera et al. • Environment International
(2025)
Background: As the health burden attributable to wildfire activity increases under climate change, it is crucial to determine which subgroups face heightened vulnerability to wildfire smoke. Marginalized communities may experience dispropor...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.envint.2025.109955
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
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
Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors
(2020)
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...
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DOI: https://doi.org/10.1021/acssensors.0c01424
John B. O. Mitchell • Wiley Interdisciplinary Reviews Computational Molecular Science
(2014)
Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics ...
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DOI: https://doi.org/10.1002/wcms.1183
PMC: 4180928
Mohssen M. Z. E. Mohammed, Muhammad Badruddin Khan, Eihab B. M. Bashier • CRC Press eBooks
(2016)
Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This...
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DOI: https://doi.org/10.1201/9781315371658
Harry Surden • Colorado Law Scholarly Commons (University of Colorado Colorado Springs)
(2014)
This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some ...
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