ArticleFrontiers in oncology2022
Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022)
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 of them syntheses that pooled it.
What it found
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Who cites it
19 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Global research trends on artificial intelligence in psychological interventions for stroke survivors: a bibliometric and visualized analysis (2000-2024).Frontiers in psychology · 2025Pooled it
- Worldwide research trends of post-subarachnoid hemorrhage epilepsy from 1995 to 2024: a bibliometric analysis.Frontiers in neurology · 2025Pooled it
- Artificial intelligence in breast ultrasound: a systematic review of research advances.Frontiers in oncology · 2025Pooled it
- Past and present: a bibliometric study on the treatment of recurrent ovarian cancer.Frontiers in pharmacology · 2024Pooled it
- The global research of artificial intelligence on Alzheimer disease: A 25-year bibliometric analysis.Medicine · 2026Article
- Research trends and hotspots of nanomaterials in Alzheimer's disease: bibliometric analysis.Discover nano · 2026Review
- Visualization and bibliometric analysis of global research trends on oral cancer screening and early diagnosis.Discover oncology · 2025Article
- Future prospects of deep learning in esophageal cancer diagnosis and clinical decision support (Review).Oncology letters · 2025Review
- Research trends on spinal muscular atrophy from 1995 to 2023: A bibliometric analysis.Medicine · 2025Review
- Current Role of Artificial Intelligence in the Management of Esophageal Cancer.Journal of clinical medicine · 2025Review
- Visual Analysis of Hyperglycemia After Enteral Nutrition in Critically Ill Patients.Journal of nutrition and metabolism · 2025Article
- Review
- Article
- Revolutionizing healthcare by use of artificial intelligence in esophageal carcinoma - a narrative review.Annals of medicine and surgery (2012) · 2023Review
- A bibliometric analysis of Mediterranean diet on cancer from 2012 to 2021.Frontiers in nutrition · 2023Article
- A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022).Frontiers in oncology · 2023Article
- An exhaustive analysis of post-traumatic brain injury dementia using bibliometric methodologies.Frontiers in neurology · 2023Article
- Research trends in endoscopic applications in early gastric cancer: A bibliometric analysis of studies published from 2012 to 2022.Frontiers in oncology · 2023Review
- Global research trends between gut microbiota and lung cancer from 2011 to 2022: A bibliometric and visualization analysis.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Using visual bibliometric analysis, the application and development of artificial intelligence in clinical esophageal cancer are summarized, and the research progress, hotspots, and emerging trends of artificial intelligence are elucidated. Methods: On April 7th, 2022, articles and reviews regarding the application of AI in esophageal cancer, published between 2000 and 2022 were chosen from the Web of Science Core Collection. To conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field, VOSviewer (version 1.6.18), CiteSpace (version 5.8.R3), Microsoft Excel 2019, R 4.2, an online bibliometric platform (http://bibliometric.com/) and an online browser plugin (https://www.altmetric.com/) were used. Results: A total of 918 papers were included, with 23,490 citations. 5,979 authors, 39,962 co-cited authors, and 42,992 co-cited papers were identified in the study. Most publications were from China (317). In terms of the H-index (45) and citations (9925), the United States topped the list. The journal "New England Journal of Medicine" of Medicine, General & Internal (IF = 91.25) published the most studies on this topic. The University of Amsterdam had the largest number of publications among all institutions. The past 22 years of research can be broadly divided into two periods. The 2000 to 2016 research period focused on the classification, identification and comparison of esophageal cancer. Recently (2017-2022), the application of artificial intelligence lies in endoscopy, diagnosis, and precision therapy, which have become the frontiers of this field. It is expected that closely esophageal cancer clinical measures based on big data analysis and related to precision will become the research hotspot in the future. Conclusions: An increasing number of scholars are devoted to artificial intelligence-related esophageal cancer research. The research field of artificial intelligence in esophageal cancer has entered a new stage. In the future, there is a need to continue to strengthen cooperation between countries and institutions. Improving the diagnostic accuracy of esophageal imaging, big data-based treatment and prognosis prediction through deep learning technology will be the continuing focus of research. The application of AI in esophageal cancer still has many challenges to overcome before it can be utilized.
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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.