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Academic Articles & Research Papers
Showing 20 of 113 academic articles
Pengsheng Hui, Yu Jiang, Jie Wang, Congxiao Wang et al. • Frontiers in Aging Neuroscience
(2024)
BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a cri...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnagi.2024.1354147
Shuchen Sun, Shuchen Sun, Shuchen Sun, Leihao Ren et al. • Frontiers in Oncology
(2022)
PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fonc.2022.879528
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ecoenv.2024.116885
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...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmars.2022.1113387
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
Rahul C. Deo • Circulation
(2015)
Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular va...
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Open Access
DOI: https://doi.org/10.1161/circulationaha.115.001593
PMC: 5831252
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
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DOI: https://doi.org/10.1145/2046684.2046692
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
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
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
Oqbah Salim Atiyah • Al-Kitab Journal for Pure Sciences
(2024)
Earthquakes are among the most dangerous natural disasters that can cause major losses to buildings and threaten human lives. The research community is very interested in the topic of earthquakes because they occur suddenly and predicting t...
DOAJ
Open Access (DOAJ)
DOI: 10.32441/kjps.09.01.p1
T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale et al. • Journal of Natural Fibers
(2025)
Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested und...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/15440478.2025.2502662
Sendhil Mullainathan, Jann Spiess • The Journal of Economic Perspectives
(2017)
Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. This similarity to ...
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DOI: https://doi.org/10.1257/jep.31.2.87
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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Open Access
Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies
(2023)
The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en16114271
Heechan Han, Boran Kim, Kyunghun Kim, Donghyun Kim et al. • Water Science and Technology
(2023)
Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an ...
DOAJ
Open Access (DOAJ)
DOI: 10.2166/wst.2023.237
Tom M. Mitchell • Communications of the ACM
(1999)
Machine learning algorithms enable discovery of important "regularities" in large data sets....
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Open Access
DOI: https://doi.org/10.1145/319382.319388