Application of Machine Learning in Lupus Research Advancement

A new study published in Lupus Science & Medicine discusses how machine learning (ML) opens new possibilities for studying lupus disease, from building predictive models, identifying new biomarkers, and developing techniques for understanding disease pathogenesis, progression and management. 

Researchers reviewed 192 studies on ML and systemic lupus erythematosus (SLE) published between 1992 and 2023. The researchers reviewed the methods for data collection, data processing and splitting, feature selection, model development and evaluation; they found most studies underreport key details on model development or that external validation had not been completed to ensure the prediction models are effective, reliable, and safe to adopt into clinical practice. 

The use of artificial intelligence (AI) has become widespread in the medical field and has already had significant influence on SLE research, but gaps and challenges remain. While AI helps facilitate discoveries that improve patient outcomes and processes, researchers need to be mindful of the ethical, governance, and regulatory considerations. Learn more about lupus research.

Read the study