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Information Extraction From FDA Drug Labeling to Enhance Product-Specific Guidance Assessment Using Natural Language Processing

Yiwen Shi, Ping Ren, Yi Zhang, Xiajing Gong et al. • Frontiers in Research Metrics and Analytics (2021)

Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frma.2021.670006

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Turdi Tohti, Jimmy Huang, Askar Hamdulla, Xing Tan • Information (2019)

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

DOAJ Open Access (DOAJ) DOI: 10.3390/info10080246

Optimising Contextual Embeddings for Meaning Conflation Deficiency Resolution in Low-Resourced Languages

Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers (2025)

Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...

DOAJ Open Access (DOAJ) DOI: 10.3390/computers14090402

Gender biases in GPT-4 short biographies.

Anna-Maria De Cesare • Linguistik Online (2026)

As has been shown in various studies considering different languages, in professional contexts women tend to be referred to differently than men. While men are typically referred to by their surname (e. g., Fermi), women are more often refe...

DOAJ Open Access (DOAJ) DOI: 10.13092/tsh3js82

Natural Language Processing

Orhan Gazi Yalçın • Apress eBooks (2020)

Natural language processing (NLP) is an interdisciplinary subfield, which has components from major fields such as linguistics, computer science, and artificial intelligence. NLP is mainly concerned with the interaction between humans and c...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-6513-0_9

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

Detection of Duplicate Defect Reports Using Natural Language Processing

Per Runeson, Magnus Alexandersson, Oskar Nyholm • ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (2007)

Defect reports are generated from various testing and development activities in software engineering. Sometimes two reports are submitted that describe the same problem, leading to duplicate reports. These reports are mostly written in stru...

OPENALEX DOI: https://doi.org/10.1109/icse.2007.32

Navigating the Ethical Terrain of AI-Generated Text Tools: A Review

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

Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr

Caglar Koylu, Chang Zhao, Wei Shao • ISPRS International Journal of Geo-Information (2019)

Thanks to recent advances in high-performance computing and deep learning, computer vision algorithms coupled with spatial analysis methods provide a unique opportunity for extracting human activity patterns from geo-tagged social media ima...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi8010045

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido • Sensors (2018)

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...

DOAJ Open Access (DOAJ) DOI: 10.3390/s18072364

Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University

Xia Zhang, Danning Xu, Ni Zhang • Applied Sciences (2022)

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing lands...

DOAJ Open Access (DOAJ) DOI: 10.3390/app12168346

Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures

Luna Ngeljaratan, Elif Ecem Bas, Mohamed A. Moustafa • Sensors (2024)

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior wo...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24051450

Intelligent Algorithm for Rock Core RQD Based on Object Detection and Image Segmentation to Suppress Noise and Vibration

Feng Xiong, Jintao Wang, Guohua Zhang, Xueming Shi et al. • Advances in Civil Engineering (2024)

In the construction of the civil engineering infrastructure, the noise and vibration are affected by the geological conditions, adopting specific construction techniques based on the geological conditions is of great significance in suppres...

DOAJ Open Access (DOAJ) DOI: 10.1155/2024/3599911

Predicting air quality index using artificial neural network: a case study of the Coimbatore region

P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering (2026)

Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44290-026-00423-z

Design of a TSR-based project learning strategy for biochemistry undergraduate teaching and research labs: a case study

Camille R. Reaux, Shelby A. Meche, Jordan M. Grider, Soundharya Dhanabal et al. • Frontiers in Education (2025)

Given the exponential growth of biochemical data and deep effect of computational methods on life sciences, there is a need to rethink undergraduate curricula. A project-oriented learning approach based on the Triangular Spatial Relationshi...

DOAJ Open Access (DOAJ) DOI: 10.3389/feduc.2024.1455173

Fundamentals of Deep Learning

P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series (2024)

This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...

OPENALEX DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001

Scalable and accurate deep learning with electronic health records

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine (2018)

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-018-0029-1 PMC: 6550175

Understanding tourist engagement with traditional dwellings through multimodal deep learning: a case study of the Gao Family Compound, Xi’an

Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications (2026)

Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...

DOAJ Open Access (DOAJ) DOI: 10.1057/s41599-026-07879-5

ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training

Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li et al. • Journal of Pharmaceutical Analysis (2025)

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jpha.2025.101317