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Showing 20 of 1,446 academic articles

Application of Convolutional Neural Network in Natural Language Processing

Wei Wang, Jianxun Gang • IEEE International Conference on Information Systems and Computer Aided Education (ICISCAE) (2018)

Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...

OPENALEX DOI: https://doi.org/10.1109/iciscae.2018.8666928

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

Sentiment Analysis and Topic Modeling of Indonesian Public Conversation about COVID-19 Epidemics on Twitter

Muhammad Habibi, Adri Priadana, Muhammad Rifqi Ma’arif • IJID (International Journal on Informatics for Development) (2021)

The World Health Organization (WHO) declared the COVID-19 outbreak has resulted in more than six million confirmed cases and more than 371,000 deaths globally on June 1, 2020. The incident sparked a flood of scientific research to help soci...

DOAJ Open Access (DOAJ) DOI: 10.14421/ijid.2021.2400

Economic Activity Forecasting Based on the Sentiment Analysis of News

Mantas Lukauskas, Vaida Pilinkienė, Jurgita Bruneckienė, Alina Stundžienė et al. • Mathematics (2022)

The outbreak of war and the earlier and ongoing COVID-19 pandemic determined the need for real-time monitoring of economic activity. The economic activity of a country can be defined in different ways. Most often, the country’s economic act...

DOAJ Open Access (DOAJ) DOI: 10.3390/math10193461

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

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

Mapping inequities in global vaccine sentiment research

Aleksandra Torbica, Deepak Sharma, Duilio Balsamo, Vittoria Offeddu et al. • BMJ Global Health (2025)

Introduction Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectiveness of immunisation programmes, with dramatic effects on morbidity and mortality for vaccine-preventable diseases. Yet, health re...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjgh-2024-018587

Feasibility of Hemolytic Disease of the Fetus and Newborn Case Ascertainment and Assessing Its Impact on Prenatal and Postnatal Outcomes: Protocol for Observational Studies

Nana A Mensah, Michael J Fassett, Nehaa Khadka, Jiaxiao M Shi et al. • JMIR Research Protocols (2025)

BackgroundHemolytic disease of the fetus and newborn (HDFN) is a rare but serious condition caused by maternal-fetal red blood cell antigen incompatibility. In an affected pregnancy, maternal immunoglobulin G antibodies cross the placenta a...

DOAJ Open Access (DOAJ) DOI: 10.2196/77836

Explainable hybrid deep learning framework for air quality index prediction in Indian cities

Priyal Singhal, Praneet Saurabh, Mayank Sharma, Jyoti Badge et al. • Discover Artificial Intelligence (2026)

Abstract Air pollution constitutes one of the most pressing environmental and public health crises of the twenty-first century, disproportionately affecting rapidly urbanising nations such as India. Accurate prediction of the Air Quality In...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02131-0

NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data

Rashmi Patel, Miguel E Rentería, Soon Nan Wee, Rajagopalan Ramaswamy et al. • BMJ Open (2022)

Purpose NeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analy...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2021-057227

National Leaders’ Usage of Twitter in Response to COVID-19: A Sentiment Analysis

Yuming Wang, Stephen M Croucher, Stephen M Croucher, Erika Pearson • Frontiers in Communication (2021)

Twitter is a powerful tool for world leaders to disseminate public health information and to reach citizens. While Twitter, like other platforms, affords world leaders the opportunity to rapidly present information to citizens, the discours...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomm.2021.732399

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

Jiaqi Fu, Chaixiu Li, Chunlan Zhou, Wenji Li et al. • Journal of Medical Internet Research (2023)

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

DOAJ Open Access (DOAJ) DOI: 10.2196/43349

Paradigm Shift in Natural Language Processing

Tianxiang Sun, Xiang-Yang Liu, Xipeng Qiu, Xuanjing Huang • Machine Intelligence Research (2022)

Abstract In the era of deep learning, modeling for most natural language processing (NLP) tasks has converged into several mainstream paradigms. For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11633-022-1331-6