ReviewHeliyon2024
Evolution and emerging trends of named entity recognition: Bibliometric analysis from 2000 to 2023.
Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Large Language Model-Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study.JMIR medical informatics · 2025Article
- Fine-tuning of language models for automated structuring of medical exam reports to improve patient screening and analysis.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.