Lupus & antiphospholipid syndrome
A machine learning model for identifying systemic lupus erythematosus through laboratory information system and electronic medical record
Authors' conclusion
Our diagnostic model based on 10 common laboratory tests identified the patients with SLE with high accuracy.
Study context
- Population
- Patients with systemic lupus erythematosus (SLE) and control immune diseasesmodeling n=862
- Outcome
- Diagnostic performance (AUC) in validation dataset
Methodological detailsmachine learning, random forest algorithm, 10-fold cross-validation, external validation dataset
- Machine learning
- Random forest algorithm
- 10-fold cross-validation
- External validation dataset
Performance
As reported in the abstract
| Test or model | AUC |
|---|---|
| SLE diagnostic model | 0.8286 |
SLE diagnostic model
AUC0.8286
Original publication
A machine learning model for identifying systemic lupus erythematosus through laboratory information system and electronic medical record. Clin Exp Rheumatol. Published 28 March 2023. doi:10.
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