Identifying valuable information within the extensive texts documented in natural language presents a significant challenge in various disciplines. Named Entity Recognition (NER), as one of the critical technologies in text data processing and mining, has become a current research hotspot. To accurately and objectively review the progress in NER, this paper employs bibliometric methods. It analyzes 1300 documents related to NER obtained from the Web of Science database using CiteSpace software. Firstly, statistical analysis is performed on the literature and journals that were obtained to explore the distribution characteristics of the literature. Secondly, the core authors in the field of NER, the development of the technology in different countries, and the leading institutions are explored by analyzing the number of publications and the cooperation network graph. Finally, explore the research frontiers, development tracks, research hotspots, and other information in this field from a scientific point of view, and further discuss the five research frontiers and seven research hotspots in depth. This paper explores the progress of NER research from both macro and micro perspectives. It aims to assist researchers in quickly grasping relevant information and offers constructive ideas and suggestions to promote the development of NER.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11066397 | PMC |
| http://dx.doi.org/10.1016/j.heliyon.2024.e30053 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing.
Proc (IEEE Int Conf Healthc Inform)
June 2024
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA.
Delirium is an acute decline or fluctuation in attention, awareness, or other cognitive function that can lead to serious adverse outcomes. Despite the severe outcomes, delirium is frequently unrecognized and uncoded in patients' electronic health records (EHRs) due to its transient and diverse nature. Natural language processing (NLP), a key technology that extracts medical concepts from clinical narratives, has shown great potential in studies of delirium outcomes and symptoms.
View Article and Find Full Text PDFMolecular epidemiology of dermatophytosis in Golestan, Iran: A cross-sectional study.
Microb Pathog
December 2024
Invasive Fungi Research Center, Communicable Diseases Institute/Department of Medical Mycology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran. Electronic address:
Keratinophilic fungi, or dermatophytes, are recognized as the predominant fungal agents responsible for superficial skin diseases globally. The identification of species of dermatophytes is crucial for both therapeutic and epidemiological considerations. The primary objective of the present study was to investigate the epidemiology of dermatophytosis among patients who sought medical attention at the medical mycology laboratory in Golestan province.
View Article and Find Full Text PDFPrimary cilia as antennas for oxygen.
Am J Physiol Cell Physiol
December 2024
Institute of Physiology, University Duisburg-Essen, Essen, Germany.
Over the last few decades, the primary cilium, an inconspicuous cell organelle, has increasingly become the focus of current research. The primary cilium is a microtubule-based, non-motile, antenna-like structure that is present on almost all mammalian cells. The ciliary membrane incorporates a large number of receptor molecules, which further characterize this cellular organelle.
View Article and Find Full Text PDFPrecision in Parsing: Evaluation of an Open-Source Named Entity Recognizer (NER) in Veterinary Oncology.
Vet Comp Oncol
December 2024
Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
Integrating Artificial Intelligence (AI) through Natural Language Processing (NLP) can improve veterinary medical oncology clinical record analytics. Named Entity Recognition (NER), a critical component of NLP, can facilitate efficient data extraction and automated labelling for research and clinical decision-making. This study assesses the efficacy of the Bio-Epidemiology-NER (BioEN), an open-source NER developed using human epidemiological and medical data, on veterinary medical oncology records.
View Article and Find Full Text PDFNamed entity recognition for de-identifying Spanish electronic health records.
Comput Biol Med
December 2024
Departamento de Lenguajes y Ciencias de la Computación, Escuela Técnica Superior de Ingeniería Informática, Universidad de Málaga, Málaga, Spain; Research Institute of Multilingual Language Technologies, Universidad de Málaga, Málaga, Spain.
Background And Objectives: There is an increasing and renewed interest in Electronic Health Records (EHRs) as a substantial information source for clinical decision making. Consequently, automatic de-identification of EHRs is an indispensable task, since their dissociation from personal data is a necessary prerequisite for their dissemination. Nevertheless, the bulk of prior research in this domain has been conducted using English EHRs, given the limited availability of annotated corpora in other languages, including Spanish.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!