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Hongyu Liu, Bo Lang • Applied Sciences
(2019)
Networks play important roles in modern life, and cyber security has become a vital research area. An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in th...
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DOI: https://doi.org/10.3390/app9204396
Julia Westermayr, Philipp Marquetand • Chemical Reviews
(2020)
Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculati...
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DOI: https://doi.org/10.1021/acs.chemrev.0c00749
PMC: 8391943
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Matthias Seeger • International Journal of Neural Systems
(2004)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...
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Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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M. Graça Pereira, Martim Santos, Renata Magalhães, Cláudia Rodrigues et al. • Behavioral Sciences
(2025)
University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bs15040505
Sumeet Dua, Xian Du • Auerbach Publications eBooks
(2011)
With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research to...
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DOI: https://doi.org/10.1201/b10867
Ari Mohammed ali Ahmed, Aree Ali Mohammed, Professor • UHD Journal of Science and Technology
(2021)
Prostate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both bi...
DOAJ
Open Access (DOAJ)
DOI: https://doi.org/10.21928/uhdjst.v5n2y2021.pp41-47
Ahmed M. Asfahani • Discover Sustainability
(2024)
Abstract This study elucidates the transformative influence of data integration on talent management in the context of evolving technological paradigms, with a specific focus on sustainable practices in human resources. Historically anchore...
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Open Access (DOAJ)
DOI: 10.1007/s43621-024-00212-7
Dimitrios Kleftogiannnis, Sonia Gavasso, Benedicte Sjo Tislevoll, Nisha van der Meer et al. • iScience
(2024)
Summary: Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for in-depth characterization of cellular heterogeneity in cancer and other diseases. Unfortunately, high-dimensional analyses of CyTOF data remain quite d...
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Open Access (DOAJ)
DOI: 10.1016/j.isci.2024.110261
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
Paul Sajda • Annual Review of Biomedical Engineering
(2006)
Machine learning offers a principled approach for developing sophisticated, automatic, and objective algorithms for analysis of high-dimensional and multimodal biomedical data. This review focuses on several advances in the state of the art...
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DOI: https://doi.org/10.1146/annurev.bioeng.8.061505.095802
C. Ramírez, Michael Greenop, Lorna Ashton, Ihtesham Ur Rehman • Applied Spectroscopy Reviews
(2020)
The way to analyze data in spectroscopy has changed substantially. At the same time, data science has evolved to the point where spectroscopy can find space to be housed, adapted and be functional. The integration of the two sciences has in...
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DOI: https://doi.org/10.1080/05704928.2020.1859525
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
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
Ming Han, Ge Sun, Paul F. Nealey, Juan J. de Pablo • npj Computational Materials
(2025)
Abstract Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41524-025-01836-7
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
Sergios Theodoridis (2015)
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabil...
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Dominic Dwyer, Peter Falkai, Nikolaos Koutsouleris • Annual Review of Clinical Psychology
(2018)
Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide...
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DOI: https://doi.org/10.1146/annurev-clinpsy-032816-045037
Zhongheng Zhang • Annals of Translational Medicine
(2016)
Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The articl...
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DOI: https://doi.org/10.21037/atm.2016.03.37
PMC: 4916348