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Development and External Validation of a Machine Learning Model for Automated Feedback Quality Assessment in Chinese Anesthesiology Residency Training

Yao L, Chen Y, Shen J, Zhang J et al. • Advances in Medical Education and Practice (2026)

Lifeng Yao, Yijun Chen, Jing Shen, Junge Zhang, Yiwei Zhang, Guojin Liang, Yiqin Ji Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespondence: Yijun Chen, De...

DOAJ Open Access (DOAJ)

A systematic literature review on spam content detection and classification

Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy • PeerJ Computer Science (2022)

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e., Facebook, Twitter, YouTube, and E-mail. ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.830

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data

Jeremy Y. Ng, Wael Abdelkader, Cynthia Lokker • BMC Complementary Medicine and Therapies (2022)

Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integr...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12906-022-03586-1

Explainable and interpretable artificial intelligence in medicine: a systematic bibliometric review

Maria Frasca, Davide La Torre, Gabriella Pravettoni, Ilaria Cutica • Discover Artificial Intelligence (2024)

Abstract This review aims to explore the growing impact of machine learning and deep learning algorithms in the medical field, with a specific focus on the critical issues of explainability and interpretability associated with black-box alg...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-024-00114-7

Natural Language Processing

Field Cady • Wiley eBooks (2017)

This chapter starts with several generic sections about natural language processing (NLP) datasets and big-picture concepts. It focuses on the core NLP concepts, and quick-and-dirty techniques to more complicated ones. The most basic concep...

OPENALEX DOI: https://doi.org/10.1002/9781119092919.ch16

Graph Neural Networks for Natural Language Processing: A Survey

Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo et al. • Foundations and Trends® in Machine Learning (2023)

Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be bes...

OPENALEX Open Access DOI: https://doi.org/10.1561/2200000096

A new image similarity metric for a perceptual and transparent geometric and chromatic assessment

Antonio Di Marino, Vincenzo Bevilacqua, Emanuel Di Nardo, Angelo Ciaramella et al. • Discover Artificial Intelligence (2026)

Abstract Full-reference image quality assessment metrics such as PSNR and SSIM misalign with human perceptual judgments on texture and shape distortions, a limitation documented across multiple benchmarks. Deep perceptual metrics such as LP...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02424-4

An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Miloš Bogdanović, Milena Frtunić Gligorijević, Jelena Kocić, Leonid Stoimenov • Applied Sciences (2025)

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15137491

Natural Language Processing Recipes

Akshay Kulkarni, Adarsha Shivananda • Apress eBooks (2019)

Implement natural language processing applications with Python in this problem-solution book. Here, coding exercises will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identi...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-4267-4

Five sources of bias in natural language processing

Dirk Hovy, Shrimai Prabhumoye • Language and Linguistics Compass (2021)

Recently, there has been an increased interest in demographically grounded bias in natural language processing (NLP) applications. Much of the recent work has focused on describing bias and providing an overview of bias in a larger context....

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/lnc3.12432 PMC: 9285808

Historical Models and Serial Sources

Michael Piotrowski • Journal of European Periodical Studies (2019)

Serial sources such as records, registers, and inventories are the ‘classic’ sources for quantitative history. Unstructured, narrative texts such as newspaper articles or reports were out of reach for historical analyses, both for practical...

DOAJ Open Access (DOAJ) DOI: 10.21825/jeps.v4i1.10226