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A Deep Backtracking Bare‐Bones Particle Swarm Optimisation Algorithm for High‐Dimensional Nonlinear Functions

Jia Guo, Guoyuan Zhou, Ke Yan, Yi Di et al. • CAAI Transactions on Intelligence Technology (2025)

ABSTRACT The challenge of optimising multimodal functions within high‐dimensional domains constitutes a notable difficulty in evolutionary computation research. Addressing this issue, this study introduces the Deep Backtracking Bare‐Bones P...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.70028

SAM-trace: a fuzzy logic approach in identifying interaction effects in the exacerbation of childhood malnutrition severity

S Shruthi, Priya Govindarajan, S. R. Shalini, Pavan John Antony • Discover Artificial Intelligence (2026)

Abstract Pediatric malnutrition remains a major global health challenge. Conventional WHO-based binary classification (Severe Acute Malnutrition (SAM) / Moderate Acute Malnutrition (MAM) relies solely on anthropometric thresholds. It fails ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01450-6

Evaluation of the accuracy of ChatGPT-4 and Gemini’s responses to the World Dental Federation’s frequently asked questions on oral health

Aysenur Arpaci, Asel Usdat Ozturk, Ismail Okur, Sanaz Sadry • BMC Oral Health (2025)

Abstract Background The field of artificial intelligence (AI) has experienced considerable growth in recent years, with the advent of technologies that are transforming a range of industries, including healthcare and dentistry. Large langua...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12903-025-06624-9

ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar • BioNLP Workshop and Shared Task (BioNLP) (2019)

Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural l...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/w19-5034

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton et al. • Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo) (2020)

We introduce Sta n z a , an open-source Python natural language processing toolkit supporting 66 human languages.Compared to existing widely used toolkits, Sta n z a features a language-agnostic fully neural pipeline for text analysis, incl...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2020.acl-demos.14

Natural Language Processing-Based Financial Time Series Forecasting: Utilizing Sentiment Analysis for Improved Stock Price Prediction

Albert Ntumba Nkongolo, Yae Olatoundji Gaba, Kafunda Katalay Pierre, Esther Matendo Mabela et al. • Journal of Innovation Information Technology and Application (2025)

This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...

DOAJ Open Access (DOAJ) DOI: 10.35970/jinita.v7i1.2290

Thyroid Ultrasound Appropriateness Identification Through Natural Language Processing of Electronic Health Records

Cristian Soto Jacome, MD, Danny Segura Torres, MD, Jungwei W. Fan, PhD, Ricardo Loor-Torres, MD et al. • Mayo Clinic Proceedings: Digital Health (2024)

Objective: To address thyroid cancer overdiagnosis, we aim to develop a natural language processing (NLP) algorithm to determine the appropriateness of thyroid ultrasounds (TUS). Patients and Methods: Between 2017 and 2021, we identified 18...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mcpdig.2024.01.001

Natural Language Processing for EHR-Based Computational Phenotyping

Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann et al. • IEEE Transactions on Computational Biology and Bioinformatics (2018)

This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis categori...

OPENALEX Open Access DOI: https://doi.org/10.1109/tcbb.2018.2849968 PMC: 6388621

Empowering text classification with NLP and explainable AI for enhanced interpretability

Sumaya Mustafa, Mariwan Hama Saeed • Journal of Electrical Systems and Information Technology (2025)

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

DOAJ Open Access (DOAJ) DOI: 10.1186/s43067-025-00273-2

A fault location method for secondary virtual circuits in smart substations based on the integration of GAE and GCN

Yuxi Wang, Yue Wang, Sha Han • Discover Artificial Intelligence (2026)

Abstract The secondary virtual circuits in smart substations enable digital and networked information exchange between devices. However, their extensive logical connections, complex structure, and implicit interdependencies pose significant...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02248-2

The Effectiveness of Arabic Stemmers Using Arabized Word Removal

Hamood ALshalabi, Sabrina Tiun, Nazlia Omar, Kamal Ali Alezabi et al. • International Journal of Information Science and Management (2022)

Other languages have influenced Arabic because of several factors, such as geographical nearness, trade communication, past Islamic conquests, science and technology, new devices, brand names, models, and fashion. As a result of these facto...

DOAJ Open Access (DOAJ)

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Ramteja Sajja, Yusuf Sermet, Ibrahim Demir • Discover Education (2026)

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44217-026-01825-y

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

Natural Language Processing in Surgery

Joseph A. Mellia, Marten N. Basta, Yoshiko Toyoda, Sammy Othman et al. • Annals of Surgery (2020)

OBJECTIVE: The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research. SUMMARY BACKGROUND DATA: Widespread implementation of electronic health...

OPENALEX DOI: https://doi.org/10.1097/sla.0000000000004419

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela et al. • IEEE Access (2024)

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3460380