Evidence map›Paper›PMID 35299747›Full record

ArticleFrontiers in oncology2022

The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis.

Zefeng Shen, Haiyang Wu, Zeshi Chen, Jintao Hu, Jiexin Pan, Jianqiu Kong, Tianxin Lin

Abstract read
In one paragraph

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 67 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Zefeng ShenDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Haiyang WuGraduate School, Tianjin Medical University, Tianjin, China.
Zeshi ChenDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Jintao HuDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Jiexin PanDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Jianqiu KongDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Tianxin LinDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer. Objective: This study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots. Methods: The articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field. Results: A total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: "Diagnosis and Prediction AI-related study", "Non-surgery AI-related study", and "Surgery AI-related study". Meanwhile, the current research hotspots were "deep learning" and "multiparametric MRI". Conclusions: Artificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years.

Indexed as

artificial intelligencebibliometricCitespaceprostate cancerVOSviewer

Identifiers

PMID35299747
PMCPMC8921533

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.