Back

Building accessible resources to empower communities: the case of the Lupus Mexican Registry

Martinez, D.; Sanchez-Aguirre, D.; Sevilla-Parra, G.; Olivares-Martinez, I.; Bravo-Garcia, F.; Hernandez-Ledesma, A. L.; Aguilar, L. A.; Dominguez-Frausto, C. A.; Garcia, J.; Pena-Ayala, A.; Alpizar-Rodriguez, D.; Tinajero-Nieto, L.; Alcauter, S.; Medina-Rivera, A.

2026-06-22 rheumatology
10.64898/2026.06.11.26355300 medRxiv
Show abstract

Motivation: Although SLE data in Latin America is increasing, clinical datasets remain difficult to access and interpret, highlighting the need for accessible tools that support data-driven precision medicine, citizen science, and public health initiatives. Results: We developed a user-friendly platform that enables us to explore LupusRGMX data through interactive queries, report generation, statistical modeling, and comprehensive insights. This resource supports community-oriented research, improves the visibility of underrepresented populations in lupus research, and provides a useful tool to enhance data accessibility. Availability and implementation: Developed in R using Shiny and bslib for interactive visualization and interface design. Available at https://github.com/NeuroGenomicsMX/Lupus_App_2.0 and https://lupusrgmx.liigh.unam.mx/shiny/lupus/

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Patterns
○ 78 papers in training set
Top 0.1%
12.1%
Similar papers in this journal
2
PLOS ONE
● 5266 papers in training set
Top 15%
12.1%
Similar papers in this journal
3
Computers in Biology and Medicine
○ 128 papers in training set
Top 0.4%
6.3%
Similar papers in this journal
4
Frontiers in Medicine
○ 120 papers in training set
Top 0.4%
5.2%
Similar papers in this journal
5
Metabolites
○ 53 papers in training set
Top 0.2%
4.9%
Similar papers in this journal
6
Viruses
○ 332 papers in training set
Top 1%
4.4%
7
Frontiers in Digital Health
○ 24 papers in training set
Top 0.2%
4.1%
8
JAMA Network Open
● 130 papers in training set
Top 1%
3.3%
50% of probability mass above
9
Rheumatology
◐ 24 papers in training set
Top 0.1%
3.3%
10
Journal of Translational Medicine
○ 57 papers in training set
Top 0.3%
2.8%
11
Frontiers in Public Health
○ 148 papers in training set
Top 3%
2.4%
12
Frontiers in Immunology
○ 638 papers in training set
Top 5%
1.9%
13
BMC Medical Research Methodology
○ 47 papers in training set
Top 0.6%
1.8%
14
PLOS Digital Health
● 106 papers in training set
Top 3%
1.8%
15
Biomedicines
○ 67 papers in training set
Top 1%
1.8%
16
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 3%
1.7%
17
Arthritis & Rheumatology
○ 36 papers in training set
Top 0.3%
1.7%
18
JMIR Medical Informatics
◐ 18 papers in training set
Top 0.5%
1.4%
19
npj Digital Medicine
○ 118 papers in training set
Top 3%
1.1%
20
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 5%
1.1%
21
Journal of Personalized Medicine
○ 28 papers in training set
Top 0.8%
1.1%
22
BMJ Open
● 601 papers in training set
Top 11%
1.1%
23
JAMIA Open
◐ 42 papers in training set
Top 1%
1.1%
24
BMC Bioinformatics
○ 457 papers in training set
Top 5%
0.9%
25
Vaccines
○ 198 papers in training set
Top 3%
0.9%
26
Genome Medicine
○ 183 papers in training set
Top 5%
0.9%
27
Diagnostics
○ 50 papers in training set
Top 2%
0.9%
28
Bioinformatics
◐ 1204 papers in training set
Top 9%
0.9%
29
Database
◐ 61 papers in training set
Top 0.9%
0.9%
30
International Journal of Molecular Sciences
○ 494 papers in training set
Top 17%
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.