Home »
Academic Articles & Research Papers
Showing 20 of 233 academic articles
Romil R. Parikh, Nishka U. Shetty, Chinar Singhal, Prachi Patel et al. • Clinics and Practice
(2026)
Objective: The aim of this study was to systematically map evidence to inform best practices for sexual and reproductive healthcare delivered via telehealth (TeleSRH) in United States-based Title X-funded clinics. Methods: We searched three...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/clinpract16010014
Alekhya Kanaparthi, Divya Dukkireddy, Hema Gopalaiah, Sathya Prakash Reddy Kesary et al. • Journal of Oral Biology and Craniofacial Research
(2020)
Background: Coronavirus diseases (COVID-19) is a public health emergency of international concern. The dental professionals are considered to be at high risk, as most of the treatments may lead to the spread of infection due to direct proxi...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jobcr.2020.08.001
Isadora Camargo Pedrino, Isadora Camargo Pedrino, Paulo Teixeira Lacava, Paulo Teixeira Lacava • Frontiers in Plant Science
(2026)
Microbial bioinputs have emerged as key components of sustainable agriculture owing to their ability to promote plant growth, improve nutrient acquisition, enhance tolerance to biotic and abiotic stresses, and suppress phytopathogens. Despi...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpls.2026.1925672
Jaehyun Lee, Jinho Kim, Woong Ko • Applied Sciences
(2019)
Electric load forecasting for buildings is important as it assists building managers or system operators to plan energy usage and strategize accordingly. Recent increases in the adoption of advanced metering infrastructure (AMI) have made b...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app9061231
Jinhyun Kim, Kyung Mee Park, Suonaa Lee, Sooji Park et al. • BMC Health Services Research
(2024)
Abstract Background Digital therapeutics (DTx) is a treatment option that uses computer software to provide evidence-based interventions for medical disorders. DTx platforms are digital services that facilitate interactions among stakeholde...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12913-024-11286-4
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
OPENALEX
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
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
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
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
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
Julia El Zini, Mariette Awad • ACM Computing Surveys
(2022)
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3529755
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
Yasir Abdelgadir Mohamed, Abdul Hakim H. M. Mohamed, Akbar Khanan, Mohamed Bashir et al. • IEEE Access
(2024)
This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclus...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3521945
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
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
Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology
(2025)
Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/biology15010042
Buhari Salisu • International Journal of AI and Advanced Computing
(2026)
The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...
DOAJ
Open Access (DOAJ)
DOI: 10.5281/zenodo.21981139
Daniela Arbeláez-Lelion, Francisco Ocaziones, Mateo José Murcia-Ramos, Samuel Salgado et al. • Cirugía Cardiovascular
(2026)
Artificial intelligence (AI) and computer vision (CV) are increasingly applied in vascular surgery for preoperative mapping and intraoperative flow/perfusion assessment, with potential to enhance safety and efficiency. However, the extent o...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.circv.2025.10.002
Xiaolong Ma, Peishun Liu, Haojie Gao, Zikang Yan et al. • IEEE Access
(2025)
In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. However, the full fine-tuning approach of...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3529807