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Academic Articles & Research Papers
Showing 20 of 405 academic articles
• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
OPENALEX
DOI: https://doi.org/10.1515/9783110670905
Jae Joon Hwang, Yun‐Hoa Jung, Bong‐Hae Cho, Min-Suk Heo • Imaging Science in Dentistry
(2019)
PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about d...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.5624/isd.2019.49.1.1
PMC: 6444007
Noor Hafizah Khairul Anuar, Mohd Amri Md Yunus, Muhammad Ariff Baharudin, Sallehuddin Ibrahim et al. • Journal of Computing Research and Innovation
(2024)
Environmental factors like temperature, solar irradiance, and rain may influence the health and productivity of stingless bees. This paper aims to investigate the best approaches applied in meliponiculture to predict beehive health and prod...
DOAJ
Open Access (DOAJ)
A. Geiss, S. J. Silva, S. J. Silva, J. C. Hardin et al. • Geoscientific Model Development
(2022)
Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrat...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/gmd-15-6677-2022
Murat Sari, Arshed A. Ahmad • International Journal of Analysis and Applications
(2019)
The aim of this article is to forecast anemia from a population through biomedical variables of individuals using the multiple linear regression model. The study is conducted in terms of dataset consisting of 539 subjects provided from bloo...
DOAJ
Open Access (DOAJ)
Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang et al. • Applied Sciences
(2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app14020774
Zhainagul Khamitova, Gulmira Omarova, Akerke Akanova, Aliya Abdukarimova et al. • Computers
(2026)
This study presents NORIA, an availability-aware multitask learning framework for clinical prediction from incomplete electronic health records (EHRs). We analyzed a public dataset of 77,724 patients and 107 numerical features. To prevent t...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/computers15100723
Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2022.01.012
Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine
(2022)
BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcvm.2022.854287
Pengfei Li, Yue Jia • Sensors
(2026)
Diameter at breast height (DBH) is a fundamental structural parameter for forest inventory and ecological analysis. However, field-based measurements (e.g., diameter tape surveys) are labor-intensive and inefficient for large-scale applicat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26092873
Tan Jiang, Shijia Zhang, Shijia Zhang, Deyou Jiang • Frontiers in Psychiatry
(2026)
BackgroundAnxiety and depressive symptoms are prevalent among university students; however, their risk factors are unlikely to operate in isolation. Instead, they may be organized in a multilevel structure that progressively approaches emot...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpsyt.2026.1809332
Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad et al. • Ecosystem Services
(2018)
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...
OPENALEX
cc-by
DOI: https://doi.org/10.1016/j.ecoser.2018.04.004
Van-Ngoc Pham, Huu-Dao Do, Thi Phuong Khue Nguyen, Van-Khanh Tran et al. • Tạp chí Khoa học và Công nghệ
(2026)
This study develops a data-driven framework using Extreme Gradient Boosting (XGBoost) to predict the Indirect Tensile Strength (ITS) of cement-treated clayey soils. Using 180 specimens with five input variables - cement content, curing time...
DOAJ
Open Access (DOAJ)
DOI: 10.31130/ud-jst.2026.24(7B).582E
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...
OPENALEX
Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Ikram Jennane, Yousef Farhaoui, Mohamed Khalifa Boutahir • Energies
(2026)
This study investigates multi-horizon forecasting of solar-based green hydrogen (H2) production in Southern Morocco (Dakhla: 23.7° N, 15.9° W; Laâyoune: 27.2° N, 13.2° W; and Guelmim: 29.0° N, 10.1° W) using daily meteorological time series...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en19173984
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
Oscar Lahuerta, Claudio Carretero, Luis Angel Barragan, Denis Navarro et al. • IEEE Open Journal of the Industrial Electronics Society
(2026)
This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/OJIES.2026.3663897
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...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
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