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Academic Articles & Research Papers
Showing 20 of 3,783 academic articles
Li Y, Yang X, Hu S • International Journal of General Medicine
(2026)
Yaling Li, Xiuhong Yang, Shuli Hu Department of Intensive Care Unit, Wuhan No. 1 Hospital, Wuhan, 430022, People’s Republic of ChinaCorrespondence: Shuli Hu, Department of Intensive Care Unit, Wuhan No. 1 Hospital, No. 215 Zhongshan Avenue,...
DOAJ
Open Access (DOAJ)
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
Khaled Hamdaoui, Ali Benzaamia, Billal Sari Ahmed, Mohamed Elhebib Guellil et al. • Journal of Engineering and Applied Science
(2025)
Abstract This study introduces a novel, interpretable machine learning framework for predicting the compression index (Cc) of clay soils by integrating three advanced gradient boosting algorithms—XGBoost, CatBoost, and LightGBM—with SHapley...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s44147-025-00727-4
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-52883-z
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
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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Simon Rogers, Mark Girolami • Chapman & Hall/CRC eBooks
(2016)
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...
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DOI: https://doi.org/10.1201/9781315382159
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
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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cc-by-nc-nd
DOI: https://doi.org/10.21037/atm.2016.03.37
PMC: 4916348
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2022/9513357
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
Rok Rajher, Mila Marinković, Polona Rus Prelog, Jure Žabkar • Scientific Reports
(2025)
Abstract Schizophrenia is a chronic and severe mental disorder that still relies on time-intensive, clinician-administered assessments. Although several automated approaches have been proposed to support diagnosis, these systems often lack ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-33129-w
Bhagyajyothi Rao, Md Gulzarull Hasan, Bandhavya Putturaya, Asha Kamath et al. • Stats
(2026)
Childhood stunting remains a major public health challenge in India and is influenced by multiple socioeconomic and environmental factors. This ecological study examined district-level correlates of childhood stunting, including Crimes Agai...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/stats9020034
ChunYu Meng, FeiFei Zuo, Shuai Liu, YuLiang Ji et al. • Frontiers in Medicine
(2026)
BackgroundThis study aimed to develop an interpretable and clinically applicable machine learning prediction model to assess the risk of adverse outcomes within one year following acute ischaemic stroke, and to establish a corresponding web...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmed.2026.1956859
Kuldeep Randhawa, Chu Kiong Loo, Manjeevan Seera, Chee Peng Lim et al. • IEEE Access
(2018)
Credit card fraud is a serious problem in financial services. Billions of dollars are lost due to credit card fraud every year. There is a lack of research studies on analyzing real-world credit card data owing to confidentiality issues. In...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2018.2806420
Yanan Wang, Jiangning Song, Tatiana T. Marquez-Lago, André Leier et al. • Scientific Reports
(2017)
Abstract Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced pro...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-017-06219-7
Paolo Graniero, Paolo Graniero, Mark Khenkin, Hans Köbler et al. • Frontiers in Energy Research
(2023)
Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fenrg.2023.1118654
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
John C. Snyder, Matthias Rupp, Katja Hansen, Klaus‐Robert Müller et al. • Physical Review Letters
(2012)
Machine learning is used to approximate density functionals. For the model problem of the kinetic energy of noninteracting fermions in 1D, mean absolute errors below 1 kcal/mol on test densities similar to the training set are reached with ...
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Open Access
DOI: https://doi.org/10.1103/physrevlett.108.253002