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An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research

Zhang, J.; Whebell, S.; Gallifant, J.; Budhdeo, S.; Mattie, H.; Lertvittayakumjorn, P.; Lopez, M. d. P.; Tiangco, B.; Gichoya, J. W.; Ashrafian, H.; Celi, L. A.; Teo, J. T.

2021-11-24 health informatics
10.1101/2021.11.23.21266758 medRxiv
Show abstract

The global clinical artificial intelligence (AI) research landscape is constantly evolving, with heterogeneity across specialties, disease areas, geographical representation, and development maturity. Continual assessment of this landscape is important for monitoring progress. Taking advantage of developments in natural language processing (NLP), we produce an end-to-end NLP pipeline to automate classification and characterization of all original clinical AI research on MEDLINE, outputting real-time results to a public, interactive dashboard (https://aiforhealth.app/).

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
npj Digital Medicine
○ 118 papers in training set
Top 0.3%
18.5%
Similar papers in this journal
2
BMJ Health & Care Informatics
● 15 papers in training set
Top 0.1%
10.6%
Similar papers in this journal
3
PLOS Digital Health
● 106 papers in training set
Top 0.7%
8.9%
Similar papers in this journal
4
Journal of the American Medical Informatics Association
◐ 71 papers in training set
Top 0.5%
6.7%
Similar papers in this journal
5
Scientific Reports
○ 3612 papers in training set
Top 25%
4.0%
Similar papers in this journal
6
Scientific Data
○ 209 papers in training set
Top 0.6%
4.0%
50% of probability mass above
7
Communications Medicine
○ 113 papers in training set
Top 0.6%
3.2%
8
Frontiers in Digital Health
○ 24 papers in training set
Top 0.2%
3.2%
9
Journal of Biomedical Informatics
○ 47 papers in training set
Top 0.6%
2.7%
10
JMIR Medical Informatics
◐ 18 papers in training set
Top 0.2%
2.6%
11
The Lancet Digital Health
○ 25 papers in training set
Top 0.2%
2.4%
12
International Journal of Medical Informatics
○ 26 papers in training set
Top 0.6%
2.1%
13
BMC Medical Informatics and Decision Making
○ 43 papers in training set
Top 0.9%
1.9%
14
BMC Medical Research Methodology
○ 47 papers in training set
Top 0.7%
1.7%
15
eBioMedicine
○ 183 papers in training set
Top 3%
1.7%
16
iScience
○ 1154 papers in training set
Top 19%
1.7%
17
GigaScience
◐ 212 papers in training set
Top 3%
1.5%
18
Healthcare
○ 17 papers in training set
Top 0.4%
1.4%
19
BMJ Open
● 601 papers in training set
Top 10%
1.3%
20
JAMIA Open
◐ 42 papers in training set
Top 1%
1.1%
21
Journal of Clinical Epidemiology
○ 31 papers in training set
Top 0.6%
1.1%
22
Journal of Medical Internet Research
◐ 87 papers in training set
Top 2%
1.1%
23
JCO Clinical Cancer Informatics
● 22 papers in training set
Top 0.5%
1.1%
24
Artificial Intelligence in Medicine
○ 17 papers in training set
Top 0.6%
1.0%
25
JAMA Network Open
● 130 papers in training set
Top 3%
1.0%
26
PLOS ONE
● 5266 papers in training set
Top 58%
0.8%
27
Patterns
○ 78 papers in training set
Top 3%
0.8%
28
Computers in Biology and Medicine
○ 128 papers in training set
Top 5%
0.8%
29
DIGITAL HEALTH
○ 17 papers in training set
Top 0.8%
0.8%
30
Clinical Trials
○ 11 papers in training set
Top 0.3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.