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Academic Articles & Research Papers
Showing 20 of 872 academic articles
Rene Y Choi, Aaron S. Coyner, Jayashree Kalpathy–Cramer, Michael F Chiang et al. • PubMed Central
(2020)
Purpose: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. Methods: A systematic literature search in PubMed was ...
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DOI: https://doi.org/10.1167/tvst.9.2.14
PMC: 7347027
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
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Open Access (DOAJ)
DOI: 10.3390/nano16030179
Kavian Khosravinia, Amirkianoosh Kiani • iScience
(2023)
Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...
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Open Access (DOAJ)
DOI: 10.1016/j.isci.2023.106438
Azim Keshavarzian Nodehi, Nasrollah Moghadam Charkari • Machine Learning with Applications
(2022)
Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context. The semantic information provided by WSD systems is highly beneficial to many task...
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Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2022.100369
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
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
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
A. Imran, Muna Elsadig, Jongsuk Ro • AIP Advances
(2026)
A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood...
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Open Access (DOAJ)
DOI: 10.1063/5.0337148
Aleksanteri Hamalainen, Aku Karhinen, Jesse Miettinen, Zacharias Dahl et al. • IEEE Access
(2025)
Rotating machines are extremely common in many industries, and their maintenance involves substantial costs and labor. Most recent studies aiming to automate fault diagnosis have focused on deep learning, but industry adoption has been slow...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3627885
Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology
(2007)
The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...
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public-domain
DOI: https://doi.org/10.1371/journal.pcbi.0030116
PMC: 1904382
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
Binbin Chen, Shengjie Long • IEEE Access
(2020)
In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3036469
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
Sebastian Raschka, Joshua M. Patterson, Corey Nolet • Information
(2020)
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the...
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DOI: https://doi.org/10.3390/info11040193
Fanny Monori, Alin Tisan • Sensors
(2026)
Odour recognition with low-cost gas sensors is challenging in open-air settings due to the non-specificity of the sensors and environmental variability. This can be mitigated by incorporating additional information into the classification p...
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Open Access (DOAJ)
DOI: 10.3390/s26082493
Nikolaos Sifakis, Antonios Kapenis, Athanasios Kolios, George Arampatzis • Energies
(2026)
Accurate, uncertainty-aware estimation of instantaneous wind turbine output is a prerequisite for integrating onshore assets into low-emission energy systems, where operational monitoring, energy-performance verification, and cooperative as...
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Open Access (DOAJ)
DOI: 10.3390/en19122897
Xiangyu Liu, Yi Han, Yanhui Du • Sensors
(2022)
With the large-scale application of the Internet of Things (IoT), security issues have become increasingly prominent. Device identification is an effective way to secure IoT environment by quickly identifying the category or model of device...
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Open Access (DOAJ)
DOI: 10.3390/s22218337
Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks
(2014)
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...
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DOI: https://doi.org/10.1017/cbo9781107298019
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