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Academic Articles & Research Papers
Showing 20 of 113 academic articles
Hezam Albaqami, Ghulam Mubashar Hassan, Amitava Datta • Sensors
(2023)
Neurological disorders have an extreme impact on global health, affecting an estimated one billion individuals worldwide. According to the World Health Organization (WHO), these neurological disorders contribute to approximately six million...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s23135960
Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid et al. • ISPRS International Journal of Geo-Information
(2024)
While socioeconomic gradients in regional health inequalities are firmly established, the synergistic interactions between socioeconomic deprivation and climate vulnerability within convenient proximity and neighbourhood locations with heal...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/ijgi13090330
Caricato A., Ficarella A., Chiodo L. Spada • E3S Web of Conferences
(2021)
Predictive maintenance is the latest frontier in the management and maintenance of many industrial assets, including aeroengines. Made possible by last decades advances in monitoring equipment and machine learning algorithms, it permits ind...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/e3sconf/202131211017
Kai-Chih Pai, Wen-Cheng Chao, Yu-Len Huang, Ruey-Kai Sheu et al. • Digital Health
(2022)
Objective The aim of this study was to develop an artificial intelligence–based model to detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and chest X-ray (CXR) data. Method The transfer learning method w...
DOAJ
Open Access (DOAJ)
DOI: 10.1177/20552076221120317
Alireza Kasaie, Suchithra Rajendran • Healthcare Analytics
(2023)
This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision ...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.health.2023.100242
Tobias Haug, Chris N Self, M S Kim • Machine Learning: Science and Technology
(2023)
Quantum computers promise to enhance machine learning for practical applications. Quantum machine learning for real-world data has to handle extensive amounts of high-dimensional data. However, conventional methods for measuring quantum ker...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/2632-2153/acb0b4
Shuai Zhang, Ke-Xin Chen, Ji-Chong Yang • European Physical Journal C: Particles and Fields
(2025)
Abstract In recent years, with the increasing luminosities of colliders, handling the growing amount of data has become a major challenge for future New Physics (NP) phenomenological research. In order to improve efficiency, machine learnin...
DOAJ
Open Access (DOAJ)
DOI: 10.1140/epjc/s10052-025-14069-1
R Vinutha, V Haripriya • International Journal of Advanced Research in Science Communication and Technology
(2024)
In order to solve challenging optimization issues, analyze data effectively, and improve the capabilities of current machine learning algorithms, quantum computing has the potential to revolutionize the area of machine learning. The propose...
OPENALEX
Open Access
DOI: https://doi.org/10.48175/ijarsct-15955
Raviraju Balappa D, Gautam Kumar Rajput • Shodh Sari
(2025)
Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...
DOAJ
Open Access (DOAJ)
DOI: https://doi.org/10.59231/SARI7840
Ziqiang Wang, Jing Zhang, Huili Chen, Xinyu Zhang et al. • Frontiers in Immunology
(2025)
BackgroundM2-like tumor-associated macrophages (TAMs) promote an immunosuppressive microenvironment and contribute to tumor progression and metastasis. However, their molecular characterization and prognostic value have not been fully explo...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fimmu.2025.1650726
Péter Wittek (2014)
Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that expla...
OPENALEX
Carlos Outeiral, Martin Strahm, Jiye Shi, Garrett M. Morris et al. • Wiley Interdisciplinary Reviews Computational Molecular Science
(2020)
Abstract Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all sci...
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DOI: https://doi.org/10.1002/wcms.1481
Vivek S Kale • CRC Press eBooks
(2018)
The origins of big data technologies come from database systems and distributed systems as well as data mining and machine learning algorithms that can process these vast amounts of data to extract the necessary knowledge. This chapter addr...
OPENALEX
DOI: https://doi.org/10.1201/9780429453311-9
Anand Handa, Ashu Sharma, Sandeep K. Shukla • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2019)
Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero‐day malware detection, threat a...
OPENALEX
DOI: https://doi.org/10.1002/widm.1306
Joydeep Bhattacharjee • Apress eBooks
(2019)
In the previous chapters, we took a look at different machine learning algorithms and then we worked on how to work with data for those algorithms. Those data sets were largely tabular, and the individual values were either numerical or cat...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-5121-8_5
John P Pestian, Henry A. Nasrallah, Paweł Matykiewicz, Aurora J. Bennett et al. • Biomedical Informatics Insights
(2010)
Suicide is the second leading cause of death among 25-34 year olds and the third leading cause of death among 15-25 year olds in the United States. In the Emergency Department, where suicidal patients often present, estimating the risk of r...
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cc-by-nc
DOI: https://doi.org/10.4137/bii.s4706
PMC: 3107011
Pratik Gajane, Pechenizkiy, Mykola • arXiv (Cornell University)
(2017)
Machine learning algorithms for prediction are increasingly being used in critical decisions affecting human lives. Various fairness formalizations, with no firm consensus yet, are employed to prevent such algorithms from systematically dis...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1710.03184
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
OPENALEX
Jalaj Thanaki (2017)
Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...
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Aditya Malte, Pratik Ratadiya • arXiv (Cornell University)
(2019)
In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1910.07370