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Showing 20 of 656 academic articles
ChunYu Meng, FeiFei Zuo, Shuai Liu, YuLiang Ji et al. • Frontiers in Medicine
(2026)
BackgroundThis study aimed to develop an interpretable and clinically applicable machine learning prediction model to assess the risk of adverse outcomes within one year following acute ischaemic stroke, and to establish a corresponding web...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmed.2026.1956859
Yanan Wang, Jiangning Song, Tatiana T. Marquez-Lago, André Leier et al. • Scientific Reports
(2017)
Abstract Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced pro...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-017-06219-7
Konstantinos G. Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson et al. • Sensors
(2018)
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...
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DOI: https://doi.org/10.3390/s18082674
PMC: 6111295
Richard F. Lyon • Cambridge University Press eBooks
(2017)
In order for a digital neocortex to learn a new skill, it will still require many iterations of education, just as a biological neocortex does, but once a single neocortex somewhere and at some time learns something, it can share that knowl...
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Open Access
DOI: https://doi.org/10.1017/9781139051699.031
Wuxin Sha, Yan Li, Shun Tang, Jie Tian et al. • InfoMat
(2021)
Abstract Polymers have been widely used in energy storage, construction, medicine, aerospace, and so on. However, the complexity of chemical composition and morphology of polymers has brought challenges to their development. Thanks to the i...
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DOI: https://doi.org/10.1002/inf2.12167
Jan Pišl, Marc Rußwurm, Lloyd Haydn Hughes, Gaston Lenczner et al. • Environmental Research Letters
(2024)
The rates of tropical deforestation remain high, resulting in carbon emissions, biodiversity loss, and impacts on local communities. To design effective policies to tackle this, it is necessary to know what the drivers behind deforestation ...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/1748-9326/ad44b2
Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand, Francesco Genovese et al. • Applied Sciences
(2025)
This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectr...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15116233
Tan Yan Lin, Pang Ying Han, Ooi Shih Yin, Khoh Wee How et al. • Journal of Engineering Technology and Applied Physics
(2023)
In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...
DOAJ
Open Access (DOAJ)
DOI: 10.33093/jetap.2023.5.2.12
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
Guang Liu, Xiaojie Wang • IEEE Access
(2019)
Stock market prediction is of great importance for financial analysis. Traditionally, many studies only use the news or numerical data for the stock market prediction. In the recent years, in order to explore their complementary, some studi...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2018.2886367
Wenbing Zhu, Weiqiang Zhang, Liming Yong • Frontiers in Psychiatry
(2026)
BackgroundExercise intervention has been associated with cognitive development in children. However, current study methods have not clarified the potential nonlinear association between exercise dosage and cognitive ability, and interpretab...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpsyt.2026.1908580
Kai Zhao, Yujia Shi, Hon-Cheong So • Pharmaceutics
(2022)
Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles fro...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/pharmaceutics14020234
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3567410
Theodore Warsavage, Fuyong Xing, Anna E Barón, William J Feser et al. • PLoS ONE
(2020)
We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0231468
Juliana Aparecida Anochi, Vinícius Albuquerque de Almeida, Haroldo Fraga de Campos Velho • Remote Sensing
(2021)
Many natural disasters in South America are linked to meteorological phenomena. Therefore, forecasting and monitoring climatic events are fundamental issues for society and various sectors of the economy. In the last decades, machine learni...
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Open Access (DOAJ)
DOI: 10.3390/rs13132468
• 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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DOI: https://doi.org/10.7551/mitpress/8291.003.0006
Fahad Ahmed Khokhar, Tommaso Zoppi, Luigi Cennini, Andrea Ceccarelli et al. • Scientific Reports
(2026)
Abstract The last decade has seen a surging opportunity for developing autonomous systems (e.g., fully autonomous driving, computer-guided robotic surgery, mobile robots for inspections and surveillance, and manufacturing robots) to relieve...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-45091-2
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
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