Evidence map›Paper›PMID 31258772›Full record

ReviewJournal of Cancer2019

Tracking knowledge evolution, hotspots and future directions of emerging technologies in cancers research: a bibliometrics review.

Xiaoyu Wang, Jingjing Guo, Dongxiao Gu, Ying Yang, Xuejie Yang, Keyu Zhu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

6 authors.

Xiaoyu WangThe 1st Affiliated Hospital, Anhui University of Traditional Chinese Medicine, Anhui 230031, China.
Jingjing GuoThe School of Management, Hefei University of Technology, Hefei, Anhui 230009, China.
Dongxiao GuThe School of Management, Hefei University of Technology, Hefei, Anhui 230009, China.
Ying YangThe School of Management, Hefei University of Technology, Hefei, Anhui 230009, China.
Xuejie YangThe School of Management, Hefei University of Technology, Hefei, Anhui 230009, China.
Keyu ZhuThe School of Management, Hefei University of Technology, Hefei, Anhui 230009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to various environmental pollution issues, cancers have become the "first killer" of human beings in the 21st century and their control has become a global strategy of human health. The increasing development of emerging information technologies has provided opportunities for prevention, early detection, diagnosis, intervention, prognosis, nursing, and rehabilitation of cancers. In recent years, the literature associated with emerging technologies in cancer has grown rapidly, but few studies have used bibliometrics and a visualization approach to conduct deep mining and reveal a panorama of this field. To explore the dynamic knowledge evolution of emerging information technologies in cancer literature, we comprehensively analyzed the development status and research hotspots in this field from bibliometrics perspective. We collected 7,136 articles (2000-2017) from the Web of Science database and visually displayed the dynamic knowledge evolution process via the analysis on time-sequence changes, spatial distribution, knowledge base, and hotspots. Much institutional cooperation occurs in this field, and research groups are relatively concentrated. BMC Bioinformatics, PLOS One, Journal of Urology, Scientific Reports, and Bioinformatics are the top five journals in this field. Research hotspots are mainly concentrated in two dimensions: the disease dimension (e.g., cancer, breast cancer, and prostate cancer), and the technical dimension (e.g., robotics, machine learning, data mining, and etc.). The emerging technologies in cancer research is fast ascending and promising. This study also provides researchers with panoramic knowledge of this field, as well as research hotspots and future directions.

Indexed as

bibliometricscancersemerging information technologyhotspotsknowledge evolution

Identifiers

PMID31258772
PMCPMC6584937

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.