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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
Yagang Zhang • InTech eBooks
(2010)
Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large...
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Open Access
DOI: https://doi.org/10.5772/217
Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce, Jeffrey Bolton et al. • Algorithms
(2023)
In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images i...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a16120567
Samuel Dzidefo Sagoe, Raymond Webrah Kazapoe, Daniel Kwayisi, Seidu Alidu et al. • Discover Soil
(2026)
Abstract Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an int...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44378-026-00229-6
Jiachen Chen, Jiachen Chen, Jiachen Chen, Kaiping Wang et al. • Frontiers in Neuroscience
(2026)
IntroductionThere are notable sex differences in the gray matter of Alzheimer’s disease(AD) patients’ brains, but current evidence is insufficient to prove these differences aid diagnosis effectively.MethodsMultivariate analysis of variance...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnins.2026.1755938
James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening
(2009)
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...
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DOI: https://doi.org/10.2174/138620709788167980
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg et al. • ACM Computing Surveys
(2020)
The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...
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Open Access
DOI: https://doi.org/10.1145/3377454
Marieth Agnes Guillen-García, Osnamir Elias Bru-Cordero, Cristian David Correa-Álvarez • Big Data and Cognitive Computing
(2026)
Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc10080274
Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information
(2022)
Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info13090412
Zexin CHEN, Tongtiegang ZHAO • Shui kexue jinzhan
(2025)
The Xin'anjiang model stands as one of the most important hydrological models. This paper develops a differentiable Xin'anjiang model coupled with the CemaNeige module（dMXAJ）under the framework of differentiable parameter learning. Specific...
DOAJ
Open Access (DOAJ)
DOI: 10.14042/j.cnki.32.1309.2025.02.003
Amjad M. Al Tobi, Ishbel Duncan • Information
(2019)
Network traffic exhibits a high level of variability over short periods of time. This variability impacts negatively on the accuracy of anomaly-based network intrusion detection systems (IDS) that are built using predictive models in a batc...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info10050159
Maher Abuhussain, Ali Hussain Alhamami, Khaled Almazam, Omar Humaidan et al. • Buildings
(2025)
This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/buildings15173031
K. W. DeGregory, Patrick K. Kuiper, Thomas DeSilvio, James D. Pleuss et al. • Obesity Reviews
(2018)
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...
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Open Access
DOI: https://doi.org/10.1111/obr.12667
PMC: 8176949
Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire et al. • Remote Sensing
(2021)
Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13030408
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
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...
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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
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
Jafar Ahmad Abed Alzubi, Anand Nayyar, Akshi Kumar • Journal of Physics Conference Series
(2018)
The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which i...
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DOI: https://doi.org/10.1088/1742-6596/1142/1/012012