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On the Challenges of Quantum Circuit Encoding Using Deep and Reinforcement Learning

Patrick Selig, Niall Murphy, David Redmond, Simon Caton • IEEE Access (2025)

Quantum computers may solve some computing tasks more efficiently than classical com- puters, but to do so requires the design of appropriate quantum circuits. However, it is hard to design even simple quantum programs. Recent results have ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3564392

Data Mining Techniques for Predictive Maintenance in Manufacturing Industries a Comprehensive Review

Chinthamu Narender, Ashish, P Mathiyalagan, B Devananda Rao et al. • ITM Web of Conferences (2025)

Predictive maintenance (PdM) is one of the major methods used in modern manufacturing to realize downtime minimization, lower the cost of maintenance and maximize machine service life by analyzing the collected data using data mining method...

DOAJ Open Access (DOAJ) DOI: 10.1051/itmconf/20257605012

The Significance of Machine Learning and Deep Learning Techniques in Cybersecurity: A Comprehensive Review

Maad Mijwil, Israa Ezzat Salem, Marwa M. Ismaeel • Iraqi Journal for Computer Science and Mathematics (2023)

People in the modern era spend most of their lives in virtual environments that offer a range of public and private services and social platforms. Therefore, these environments need to be protected from cyber attackers that can steal data o...

DOAJ Open Access (DOAJ) DOI: 10.52866/ijcsm.2023.01.01.008

Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review

Fábio Eid Morooka, Adalberto Manoel Junior, Tiago F. A. C. Sigahi, Jefferson de Souza Pinto et al. • Machine Learning and Knowledge Extraction (2023)

Applications of deep learning (DL) in autonomous vehicle (AV) projects have gained increasing interest from both researchers and companies. This has caused a rapid expansion of scientific production on DL-AV in recent years, encouraging res...

DOAJ Open Access (DOAJ) DOI: 10.3390/make5030041

Computational linguistics and discourse complexology: Paradigms and research methods

Valery Dmitrievich Solovyev, Marina Ivanovna Solnyshkina, Danielle S. McNamara • Russian Journal of Linguistics (2022)

The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic ana...

DOAJ Open Access (DOAJ) DOI: 10.22363/2687-0088-31326

Classifying Characteristics of Opioid Use Disorder From Hospital Discharge Summaries Using Natural Language Processing

Melissa N. Poulsen, Philip J. Freda, Vanessa Troiani, Anahita Davoudi et al. • Frontiers in Public Health (2022)

BackgroundOpioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of O...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpubh.2022.850619

Natural language processing with transformers: a review

Georgiana Țucudean, Marian Bucos, Bogdan Drăgulescu, Cătălin Daniel Căleanu • PeerJ Computer Science (2024)

Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the ma...

OPENALEX cc-by DOI: https://doi.org/10.7717/peerj-cs.2222 PMC: 11322986

Advancements in natural language processing: Implications, challenges, and future directions

Supriyono Supriyono, Aji Prasetya Wibawa, Suyono Suyono, Fachrul Kurniawan • Telematics and Informatics Reports (2024)

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.teler.2024.100173

BioBBC: a multi-feature model that enhances the detection of biomedical entities

Hind Alamro, Takashi Gojobori, Magbubah Essack, Xin Gao • Scientific Reports (2024)

Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-58334-x

A systematic review of natural language processing applied to radiology reports

Arlene Casey, Emma Davidson, Michael Poon, Hang Dong et al. • BMC Medical Informatics and Decision Making (2021)

BACKGROUND: Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to r...

OPENALEX cc-by DOI: https://doi.org/10.1186/s12911-021-01533-7 PMC: 8176715

On Application of Natural Language Processing in Machine Translation

Zhaorong Zong, Changchun Hong • International Conference on Mechanical, Control and Computer Engineering (ICMCCE) (2018)

Natural language processing is the core of machine translation. In the history, its development process is almost the same as machine translation, and the two complement each other. This article compares the natural language processing of s...

OPENALEX DOI: https://doi.org/10.1109/icmcce.2018.00112

Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies

Andrea Cadeddu, Alessandro Chessa, Vincenzo De Leo, Gianni Fenu et al. • Information (2024)

Online platforms have become the primary means for travellers to search, compare, and book accommodations for their trips. Consequently, online platforms and revenue managers must acquire a comprehensive comprehension of these dynamics to f...

DOAJ Open Access (DOAJ) DOI: 10.3390/info15070398