Diagnostic Accuracy of AI-Based Symptom Checker and Web-Based Self-Referral Tool in Rheumatology
Key Findings
The study aimed to evaluate the diagnostic accuracy of a mobile artificial intelligence (AI)-based symptom checker (Ada) and a web-based self-referral tool (Rheport) in identifying inflammatory rheumatic diseases (IRDs).
Results showed that both tools demonstrated overall diagnostic accuracies of 52% to 63% for IRDs, with varied sensitivity and specificity. Ada performed better in identifying rheumatoid arthritis compared to other diagnoses.
Implications
The study highlights that the diagnostic accuracies of both tools for IRDs were not promising in a high-prevalence patient population. Additionally, the findings suggest that these digital diagnostic decision support systems (DDSSs) may lead to a misuse of scarce health care resources, signaling the need for stringent regulation and improvements to ensure safety and efficacy.
Value in Clinical Practice
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