| Title |
A bibliometric analysis of natural language processing in medical research
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, March 2018
|
| DOI | 10.1186/s12911-018-0594-x |
| Pubmed ID | |
| Authors |
Xieling Chen, Haoran Xie, Fu Lee Wang, Ziqing Liu, Juan Xu, Tianyong Hao |
| Abstract |
Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance to conduct a deep analysis to understand the recent development of NLP-empowered medical research field. However, limited study examining the research status of this field could be found. Therefore, this study aims to quantitatively assess the academic output of NLP in medical research field. We conducted a bibliometric analysis on NLP-empowered medical research publications retrieved from PubMed in the period 2007-2016. The analysis focused on three aspects. Firstly, the literature distribution characteristics were obtained with a statistics analysis method. Secondly, a network analysis method was used to reveal scientific collaboration relations. Finally, thematic discovery and evolution was reflected using an affinity propagation clustering method. There were 1405 NLP-empowered medical research publications published during the 10 years with an average annual growth rate of 18.39%. 10 most productive publication sources together contributed more than 50% of the total publications. The USA had the highest number of publications. A moderately significant correlation between country's publications and GDP per capita was revealed. Denny, Joshua C was the most productive author. Mayo Clinic was the most productive affiliation. The annual co-affiliation and co-country rates reached 64.04% and 15.79% in 2016, respectively. 10 main great thematic areas were identified including Computational biology, Terminology mining, Information extraction, Text classification, Social medium as data source, Information retrieval, etc. CONCLUSIONS: A bibliometric analysis of NLP-empowered medical research publications for uncovering the recent research status is presented. The results can assist relevant researchers, especially newcomers in understanding the research development systematically, seeking scientific cooperation partners, optimizing research topic choices and monitoring new scientific or technological activities. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 123 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 11% |
| Student > Master | 14 | 11% |
| Student > Ph. D. Student | 8 | 7% |
| Lecturer | 8 | 7% |
| Student > Bachelor | 6 | 5% |
| Other | 25 | 20% |
| Unknown | 48 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 14% |
| Medicine and Dentistry | 9 | 7% |
| Social Sciences | 8 | 7% |
| Engineering | 7 | 6% |
| Biochemistry, Genetics and Molecular Biology | 5 | 4% |
| Other | 21 | 17% |
| Unknown | 56 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 March 2018.
All research outputs
#15,139,694
of 23,283,373 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,253
of 2,023 outputs
Outputs of similar age
#202,045
of 333,267 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 8 outputs
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So far Altmetric has tracked 2,023 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.