
AI Triages Rheumatology Referrals as Well as Doctors
A new study shows that smart prompting makes cheap, small AI models triage patients just as safely as expensive ones.
Discover the newest research about AI innovations in π Rheumatology.

A new study shows that smart prompting makes cheap, small AI models triage patients just as safely as expensive ones.

A new human-AI framework shows that the best way to clean up messy electronic health records is to let algorithms and doctors correct each other.

Automating lupus tracking with open-source language models could finally bring standardized disease monitoring to busy clinics.

Global trends in autoimmunity & immunodeficiency reveal regional disparities in diagnosis & outcomes. ππ Key findings from PubMed article!

Critical view on AI in rheumatology: small datasets, overfitting, and real-world failures. ππ€

Distinct immune and metabolic profiles in ACPA-negative vs. ACPA-positive rheumatoid arthritis revealed through multi-omic blood analysis. π©Έπ¬

Machine learning predicts difficult-to-treat rheumatoid arthritis with 0.606-0.747 accuracy. Key features include DAS28-ESR and HAQ. ππ€

Exploring childhood vasculitis: recent advances in diagnosis, treatment, and future directions. ππ©Ί

Integrating AI in medical training enhances skills for future doctors. Key insights from Tan et al. (2025) reveal transformative potential. π€π

Exploring biomarkers for rheumatoid arthritis treatment response: 10-15% of patients may benefit from early cellular therapies. π¬π