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Academic Articles & Research Papers
Showing 20 of 2,986 academic articles
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
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 ...
DOAJ
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
Zhixin Lu, Brian R. Hunt, Edward Ott • Chaos An Interdisciplinary Journal of Nonlinear Science
(2018)
A machine-learning approach called "reservoir computing" has been used successfully for short-term prediction and attractor reconstruction of chaotic dynamical systems from time series data. We present a theoretical framework that describes...
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Open Access
DOI: https://doi.org/10.1063/1.5039508
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
Bernd Bischl, Michel Lang, Lars Kotthoff, Patrick Schratz et al. (2013)
Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensiti...
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Open Access
DOI: https://doi.org/10.32614/cran.package.mlr
Naga Ramesh Palakurti, Nageswararao Kanchepu • Advances in systems analysis, software engineering, and high performance computing book series
(2024)
This chapter delves into the core principles of machine learning, offering practical insights for effective data processing. From foundational concepts to advanced techniques, the narrative unfolds as a comprehensive guide for harnessing th...
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DOI: https://doi.org/10.4018/979-8-3693-2909-2.ch002
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...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26082493
Qingfeng Sun, Kai Zhang, Yuanlong Xu, Mengmei Luo et al. • BMC Infectious Diseases
(2025)
Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...
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Open Access (DOAJ)
DOI: 10.1186/s12879-025-11998-w
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...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s22218337
Zhao D, Qin D, Yin L, Yang Q • Pharmacogenomics and Personalized Medicine
(2023)
Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...
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Open Access (DOAJ)
Nathan A. Brooks, Ankur Puri, Sanya Garg, Swapnika Nag et al. • Scientific Reports
(2021)
Abstract Population-level data have suggested that bacille Calmette-Guerin (BCG) vaccination may lessen the severity of Coronavirus Disease-19 (COVID-19) prompting clinical trials in this area. Some reports have demonstrated conflicting res...
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Open Access (DOAJ)
DOI: 10.1038/s41598-020-80787-z
Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics
(2014)
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....
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DOI: https://doi.org/10.3389/fninf.2014.00014
PMC: 3930868
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
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DOI: https://doi.org/10.1017/cbo9780511804779
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
Bill Fulkerson, Donald Michie, David J. Spiegelhalter, C. C. Taylor • Technometrics
(1995)
Survey of previous comparisons and theoretical work descriptions of methods dataset descriptions criteria for comparison and methodology (including validation) empirical results machine learning on machine learning....
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DOI: https://doi.org/10.1080/00401706.1995.10484383
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
Marc Claesen, Bart De Moor • arXiv (Cornell University)
(2015)
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based o...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1502.02127
Anzar Abbas, Vijay Yadav, Emma Smith, Elizabeth Ramjas et al. • Digital Biomarkers
(2021)
Introduction: Motor abnormalities have been shown to be a distinct component of schizophrenia symptomatology. However, objective and scalable methods for assessment of motor functioning in schizophrenia are lacking. Advancements in machine ...
DOAJ
Open Access (DOAJ)
DOI: 10.1159/000512383