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AI-generated draft replies to patient messages: exploring effects of implementation

Charlotte M. H. H. T. Bootsma-Robroeks, Charlotte M. H. H. T. Bootsma-Robroeks, Jessica D. Workum, Jessica D. Workum et al. • Frontiers in Digital Health (2025)

IntroductionThe integration of Large Language Models (LLMs) in Electronic Health Records (EHRs) has the potential to reduce administrative burden. Validating these tools in real-world clinical settings is essential for responsible implement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdgth.2025.1588143

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

Data-driven materials research enabled by natural language processing and information extraction

Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova et al. • Applied Physics Reviews (2020)

Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly hetero...

OPENALEX other-oa DOI: https://doi.org/10.1063/5.0021106

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

Wang, Jing, Deng, Huan, Liu, Bangtao, Hu, Anbin et al. • Journal of Medical Internet Research (2020)

BackgroundNatural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and incr...

DOAJ Open Access (DOAJ) DOI: 10.2196/16816

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

Fast Exploring Literature by Language Machine Learning for Perovskite Solar Cell Materials Design

Lei Zhang, Yiru Huang, Leiming Yan, Jinghao Ge et al. • Advanced Intelligent Systems (2024)

Making computers automatically extract latent scientific knowledge from literature is highly desired for future materials and chemical research in the artificial intelligence era. Herein, the natural language processing (NLP)‐based machine ...

DOAJ Open Access (DOAJ) DOI: 10.1002/aisy.202300678

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports (2021)

Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-021-88027-8

Valorisation of agri-food by-products into bioactive compounds: Green extraction, microbial biotransformation and circular biorefinery strategies

Arjun Mohanakumar, Massimiliano Rinaldi, Jasmine Hadj Saadoun, Camilla Lazzi et al. • Applied Food Research (2026)

Agri-food processing generates large volumes of by-products that remain insufficiently exploited despite their content of phenolic compounds, peptides, polysaccharides, carotenoids, dietary fibres and other functional constituents. These si...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.afres.2026.102511

Handbook of Natural Language Processing

Nitin Indurkhya, Fred J. Damerau • Chapman & Hall/CRC eBooks (2010)

The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter ...

OPENALEX DOI: https://doi.org/10.1201/9781420085938

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Ali Haider, Ghulam Muhammad, Talha Ahmed Khan, Kushsairy Kadir et al. • Scientific Reports (2025)

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-18886-y

DIAGNOSTICS OF RUSTS AND SPOTTS OF WHEAT USING COMPUTER VISION METHODS

Irina V. Arinicheva, Igor V. Arinichev, Galina V. Volkova, Sergey V. Polyanskikh • Siberian Journal of Life Sciences and Agriculture (2022)

Purpose. To investigate the possibility of diagnosing yellow and brown rust (Puccinia striiformis f. sp. tritici West. Puccinia triticina f. sp. tritici Erikss), yellow spot (Pyrenophora tritici-repentis (Died.) Drechsler) on wheat leaves f...

DOAJ Open Access (DOAJ) DOI: 10.12731/2658-6649-2022-14-1-248-261

Studying the causes of humidity fluctuations in food products within industrial environments

Elouanes Khelifi, Amir Saki, Sousso Kelouwani, Usef Faghihi • Applied Food Research (2026)

The production of processed foods and animal nutrition requires precise control over product characteristics to ensure consistent quality. Unexpected fluctuations in key parameters, particularly humidity, can lead to significant financial l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.afres.2026.102698

A novel nondestructive detection approach for seed cotton lint percentage using deep learning

Lijie Geng, Pengji Yan, Zhikun Ji, Chunyu Song et al. • Journal of Cotton Research (2024)

Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42397-024-00178-x

Automated estimation of cementitious sorptivity via computer vision

Hossein Kabir, Jordan Wu, Sunav Dahal, Tony Joo et al. • Nature Communications (2024)

Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1038/s41467-024-53993-w PMC: 11568162