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Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study
Tran BX, Tran BX, Vu GT, Ha GH, Vuong QH, Ho MT, Vuong TT, La VP et al.. Journal of clinical medicine, 2019-03-14
Topic: Brain imaging, connectivity and assessment
The increasing application of Artificial Intelligence (AI) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI in health and medicine. A total of 27,451 papers that were published between 1977 and 2018 (84.6% were dated 2008⁻2018) were retrieved from the Web of Science platform. The descriptive analysis examined the publication volume, and authors and countries collaboration. A global network of authors' keywords and content analysis of related scientific literature highlighted major techniques, including Robotic, Machine learning, Artificial neural network, Artificial intelligence, Natural language process, and their most frequent applications in Clinical Prediction and Treatment. The number of cancer-related publications was the highest, followed by Heart Diseases and Stroke, Vision impairment, Alzheimer's, and Depression. Moreover, the shortage in the research of AI application to some high burden diseases suggests future directions in AI research. This study offers a first and comprehensive picture of the global efforts directed towards this increasingly important and prolific field of research and suggests the development of global and national protocols and regulations on the justification and adaptation of medical AI products.
Key findings
- The descriptive analysis examined the publication volume, and authors and countries collaboration.
- A global network of authors' keywords and content analysis of related scientific literature highlighted major techniques, including Robotic, Machine learning, Artificial neural network, Artificial intelligence, Natural language process, and their most frequent applications in Clinical Prediction and Treatment.
- The number of cancer-related publications was the highest, followed by Heart Diseases and Stroke, Vision impairment, Alzheimer's, and Depression.
- Moreover, the shortage in the research of AI application to some high burden diseases suggests future directions in AI research.
- This study offers a first and comprehensive picture of the global efforts directed towards this increasingly important and prolific field of research and suggests the development of global and national protocols and regulations on the justification and adaptation of medical AI products.
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Study details
- Participants27,451
- Effect size84.6%
- Evidence strengthLow
How this study scored 57/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 33 of the 58 points we could judge it on, which is 57 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of clinical medicine) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2019 — within 10 year(s) of the newest study here |
| Sample size | 4 / 4 | 27,451 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 30875745) |
| Free to read | 2 / 2 | Free to read |
| Points | 33 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 33 of the 58 points we could judge it on is 57 out of 100. |
| Total | 57 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Tran, B. X., Vu, G. T., Ha, G. H., Vuong, Q. H., Ho, M. T., Vuong, T. T., et al. (2019). Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study. Journal of clinical medicine. https://doi.org/10.3390/jcm8030360
Vancouver
Tran BX, Vu GT, Ha GH, Vuong QH, Ho MT, Vuong TT, et al. Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study. Journal of clinical medicine. 2019. doi:10.3390/jcm8030360. PMID: 30875745.
BibTeX
@article{tran2019-30875745,
author = {Tran, B. X. and Vu, G. T. and Ha, G. H. and Vuong, Q. H. and Ho, M. T. and Vuong, T. T. and La, V. P. and others},
title = {{Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study}},
journal = {Journal of clinical medicine},
year = {2019},
doi = {10.3390/jcm8030360},
pmid = {30875745},
url = {https://doi.org/10.3390/jcm8030360}
}
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