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Academic Articles & Research Papers
Showing 20 of 1,623 academic articles
Caroline W. Grant, Jerry Li, Swan Lin, Dana Nickens et al. • Clinical and Translational Science
(2025)
ABSTRACT Patient outcomes in advanced renal cell carcinoma (RCC) remain poor, with five‐year survival rates ranging from ~10% to 30%. Early projections of therapeutic outcomes could optimize precision medicine and accelerate drug developmen...
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Open Access (DOAJ)
DOI: 10.1111/cts.70348
Christopher E. Lawson, Jose Manuel Martí, Tijana Radivojević, Sai Vamshi R. Jonnalagadda et al. • Metabolic Engineering
(2020)
Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing ...
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DOI: https://doi.org/10.1016/j.ymben.2020.10.005
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
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
Michael J. Bianco, Peter Gerstoft, James A. Traer, Emma Reeves Ozanich et al. • The Journal of the Acoustical Society of America
(2019)
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transformative potential of machine learning (ML), including deep lear...
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Open Access
DOI: https://doi.org/10.1121/1.5133944
Pablo Neirz, Héctor Allende, Carolina Saavedra • Scientific Reports
(2026)
Abstract High predictive accuracy is frequently misinterpreted as evidence of causal understanding or population-level signal. Models can exploit spurious correlations, confounding, or protocol-induced artefacts, while post-hoc explanations...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-52883-z
Zheng Wang, Michael F. P. O’boyle • Proceedings of the IEEE
(2018)
In the last decade, machine-learning-based compilation has moved from an obscure research niche to a mainstream activity. In this paper, we describe the relationship between machine learning and compiler optimization and introduce the main ...
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Open Access
DOI: https://doi.org/10.1109/jproc.2018.2817118
Xiaoling Wei, Yongbao Feng, Xiaoxia Han, Zhenxin He • International Transactions on Electrical Energy Systems
(2022)
At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by...
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Open Access (DOAJ)
DOI: 10.1155/2022/9513357
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
Neusa R. Adão Martins, Neusa R. Adão Martins, Simon Annaheim, Christina M. Spengler et al. • Frontiers in Physiology
(2021)
The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems...
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Open Access (DOAJ)
DOI: 10.3389/fphys.2021.790292
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...
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Open Access (DOAJ)
DOI: 10.3389/fpsyt.2026.1908580
Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science
(2023)
Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.1677
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
S. Mostafa Mousavi, Gregory C. Beroza • Annual Review of Earth and Planetary Sciences
(2022)
Machine learning (ML) is a collection of methods used to develop understanding and predictive capability by learning relationships embedded in data. ML methods are becoming the dominant approaches for many tasks in seismology. ML and data m...
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DOI: https://doi.org/10.1146/annurev-earth-071822-100323
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
Minh Ly Duc, Petr Bilik • Applied Sciences
(2023)
Electronic equipment is indispensable in the industrial 4.0 era. Electromagnetic Compatibility issues with electronic devices are increasingly concerning. The phenomenon of electromagnetic field compatibility is getting higher and higher. T...
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Open Access (DOAJ)
DOI: 10.3390/app13021005
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...
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Open Access (DOAJ)
DOI: 10.3390/app16178708
Alberto Gil-Maciá, J. Enrique Sierra-García, Matilde Santos • Machine Learning with Applications
(2026)
Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system...
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Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2026.100919
Tomoya Maeda, Junichiro Iwasawa, Hazuki Kotani, Natsue Sakata et al. • Nature Communications
(2020)
Understanding evolutionary constraints in antibiotic resistance is crucial for prediction and control. Here, the authors use high-throughput laboratory evolution of Escherichia coli alongside machine learning to identify trade-off relations...
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Open Access (DOAJ)
DOI: 10.1038/s41467-020-19713-w
Willian Borges De Lemos, Lucas De Angelo Martins Ribeiro, Vanessa Telles Da Silva, Alessandro De Lima Bicho et al. • IEEE Access
(2025)
Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support tasks such as node classification, link prediction ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3643796