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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

Assessing perception and equity of cultural ecosystem services in urban parks using social media data

Yu Zhang, Lin Zhao, Shiyuan Hu • Scientific Reports (2025)

Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-18288-0

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Asefeh Asemi, Rajab Kiani Shahvandy, Mahdi Houshangi • International Journal of Information Management Data Insights (2026)

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jjimei.2026.100396

DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN

Aigerim Mansurova, Aliya Nugumanova, Zhansaya Makhambetova • Scientific Journal of Astana IT University (2023)

Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream tasks. Despite their ...

DOAJ Open Access (DOAJ) DOI: 10.37943/15XNDZ6667

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial (2024)

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

DOAJ Open Access (DOAJ)

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Rishi V. Parikh, Alan S. Go, Ankeet S. Bhatt, Thida C. Tan et al. • Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease (2023)

Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...

DOAJ Open Access (DOAJ) DOI: 10.1161/JAHA.122.029736

Training‐Efficient Personalised Knee Joint Moment Estimation via an Incremental Broad Learning System

Guoyu Zuo, Minghui Zhang, Jingwei Ren, Qifei Wu et al. • CAAI Transactions on Intelligence Technology (2026)

ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.70165

MedScan, a natural language processing engine for MEDLINE abstracts

Svetlana Novichkova, Sergei Egorov, Nikolai Daraselia • Bioinformatics (2003)

MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely us...

OPENALEX Open Access DOI: https://doi.org/10.1093/bioinformatics/btg207

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca et al. • Journal of Medical Internet Research (2020)

BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...

OPENALEX cc-by DOI: https://doi.org/10.2196/15708 PMC: 8132982

Data augmentation techniques in natural language processing

Lucas Francisco Amaral Orosco Pellicer, Taynan Maier Ferreira, Anna Helena Reali Costa • Applied Soft Computing (2022)

Data Augmentation (DA) methods – a family of techniques designed for synthetic generation of training data – have shown remarkable results in various Deep Learning and Machine Learning tasks. Despite its widespread and successful adoption w...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.asoc.2022.109803

Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine

Jonas Rieger, Kostiantyn Yanchenko, Mattes Ruckdeschel, Gerret von Nordheim et al. • Studies in Communication, Media (2024)

Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the ...

DOAJ Open Access (DOAJ) DOI: 10.5771/2192-4007-2024-1-72

Analyzing Sentiments in eLearning: A Comparative Study of Bangla and Romanized Bangla Text Using Transformers

Md Akash Rahman, Manoara Begum, Tanjim Mahmud, Mohammad Shahadat Hossain et al. • IEEE Access (2024)

In the modern world, learning is becoming increasingly critical due to rapid technological breakthroughs, which highlight the need for continuous skill development in both the personal and professional spheres. As a result, eLearning is a c...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3419024

Machine Reading Comprehension for the Tamil Language With Translated SQuAD

Anton Vijeevaraj Ann Sinthusha, Eugene Y. A. Charles, Ruvan Weerasinghe • IEEE Access (2025)

Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3530949

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Turdi Tohti, Jimmy Huang, Askar Hamdulla, Xing Tan • Information (2019)

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

DOAJ Open Access (DOAJ) DOI: 10.3390/info10080246

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi • PeerJ Computer Science (2025)

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.2669

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

Ming-I. Chen, Ying-Lin Hsu, Yi-Hsin Chen • Scientific Reports (2026)

Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-57682-0