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Showing 20 of 2,986 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
Kuldeep Randhawa, Chu Kiong Loo, Manjeevan Seera, Chee Peng Lim et al. • IEEE Access
(2018)
Credit card fraud is a serious problem in financial services. Billions of dollars are lost due to credit card fraud every year. There is a lack of research studies on analyzing real-world credit card data owing to confidentiality issues. In...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2018.2806420
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
Pavlo O. Dral • The Journal of Physical Chemistry Letters
(2020)
As the quantum chemistry (QC) community embraces machine learning (ML), the number of new methods and applications based on the combination of QC and ML is surging. In this Perspective, a view of the current state of affairs in this new and...
OPENALEX
Open Access
DOI: https://doi.org/10.1021/acs.jpclett.9b03664
Pat Langley B, Herbert A. Simon • Communications of the ACM
(1995)
M achine learning is the study of computational methods for improving performance by mechanizing the acquisition of knowledge from experience. Expert performance requires much domain-specific knowledge, and knowledge engineering has produce...
OPENALEX
DOI: https://doi.org/10.1145/219717.219768
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
Arvind Kumar Tiwari • IGI Global eBooks
(2019)
Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...
OPENALEX
DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003
Zetao Yan • Egyptian Informatics Journal
(2025)
Portfolio optimization is a process that involves distribution of capital with the purpose of maximizing returns and at the same time minimizing risks. The current paper discusses the use of Transformer networks in supervised learning for p...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.eij.2025.100839
Rodolphe Jantzen, Rodolphe Jantzen, Mathieu Maltais, Mathieu Maltais et al. • Frontiers in Public Health
(2022)
IntroductionThe objective of this study was to characterize the combinations of demographic and socioeconomic characteristics associated to the unwillingness to receive the COVID-19 vaccines during the 2021 Quebec's vaccination campaign.Mat...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpubh.2022.756037
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
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
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
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...
OPENALEX
DOI: https://doi.org/10.1017/9781108679930
Stephen Marsland • Chapman & Hall/CRC eBooks
(2011)
Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is re...
OPENALEX
DOI: https://doi.org/10.1201/9781420067194
Steven L. Brunton, J. Nathan Kutz • Cambridge University Press eBooks
(2022)
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering...
OPENALEX
DOI: https://doi.org/10.1017/9781009089517.019
Mahmood Matin, Mohammad Azadi • International Journal of Lightweight Materials and Manufacture
(2024)
The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens wit...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ijlmm.2024.04.004
Madeleine J Smith, Sandra Reeder, Fiona Waugh, Shobi Sivathamboo et al. • JMIR AI
(2026)
Abstract
BackgroundAntiseizure medications (ASMs) are the mainstay of epilepsy treatment; however, there is currently no reliable way to predict which medication will be most effective for an individual patient. Machine learning...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/85047
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
Shihao Gu, Bryan Kelly, Dacheng Xiu • Review of Financial Studies
(2020)
Abstract We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, i...
OPENALEX
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DOI: https://doi.org/10.1093/rfs/hhaa009