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Academic Articles & Research Papers
Showing 20 of 785 academic articles
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
Jakob Mannstadt, Arash Rahimi‐Iman • Advanced Sensor Research
(2025)
Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/adsr.70009
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences
(2022)
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1016/j.paerosci.2022.100849
Tanattrin Bunnag • Forecasting
(2026)
Geopolitical uncertainty may affect financial markets, but its incremental value for forecasting emerging-market stock returns remains unclear. Using monthly data from January 1990 to July 2026, this study compares ARIMA-GARCH and ARIMAX-GA...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/forecast8050087
Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data
(2026)
Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40537-026-01475-9
Romulus Costache, Hazem Ghassan Abdo, Arun Pratap Mishra, Subodh Chandra Pal et al. • Geomatics, Natural Hazards & Risk
(2023)
AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/19475705.2023.2281241
Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports
(2025)
Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-19922-7
Yajing Tian, Yuyang Wang, Shasha Yin, Jia Lu et al. • Energies
(2024)
U-tube steam generators (UTSGs) are crucial in nuclear power plants, serving as the interface between the primary and secondary coolant loops. UTSGs ensure efficient heat exchange, operational stability, and safety, directly impacting the p...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en17163916
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
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
Y. Y. Abdullahi, A. S. Nur, A. Sale • Journal of Applied Sciences and Environmental Management
(2025)
Machine learning provides more verbose algorithms capable of accurately predicting, classifying groups as needed. Consequently, the objective of this paper is to assess the benchmarking of Supervised Machine Learning Algorithms of K-Nearest...
DOAJ
Open Access (DOAJ)
Mikhail Ivanenko, Damian Wanta, Waldemar T. Smolik, Przemysław Wróblewski et al. • Life
(2024)
This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/life14030419
Caroline W. Grant, Jerry Li, Swan Lin, Dana Nickens et al. • Clinical and Translational Science
(2025)
ABSTRACT Patient outcomes in advanced renal cell carcinoma (RCC) remain poor, with five‐year survival rates ranging from ~10% to 30%. Early projections of therapeutic outcomes could optimize precision medicine and accelerate drug developmen...
DOAJ
Open Access (DOAJ)
DOI: 10.1111/cts.70348
Sagar Chokshi, Piyush Gohil, Vijay Parmar, Vijaykumar Chaudhary • Mechanics of Advanced Composite Structures
(2025)
Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computationa...
DOAJ
Open Access (DOAJ)
DOI: 10.22075/macs.2024.33874.1664
Zhiqiang Gong, Ping Zhong, Weidong Hu • IEEE Access
(2019)
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/access.2019.2917620
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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cc-by-nc-nd
DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
Ildar M. Ishkulov, Irik G. Fattakhov • Записки Горного института
(2025)
The problem of timely and accurate evaluation of well integrity is becoming increasingly relevant in the context of mature field development, high wellstream water cut, and a growing number of old wells. For production casing diagnostics, g...
DOAJ
Open Access (DOAJ)
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
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...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3377454
Michael J. Bianco, Peter Gerstoft, James A. Traer, Emma Reeves Ozanich et al. • The Journal of the Acoustical Society of America
(2019)
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transformative potential of machine learning (ML), including deep lear...
OPENALEX
Open Access
DOI: https://doi.org/10.1121/1.5133944