Bridging the Gap Between Artificial Intelligence and Clinical Readiness in Endometriosis Diagnosis: A Systematic Review

The authors aim to systematically evaluate the methodological quality and diagnostic performance of artificial intelligence applications in diagnosing endometriosis through imaging and clinical symptoms. Their review finds that while AI models show promising diagnostic accuracies, significant limitations exist, including clinical heterogeneity and biases in study populations, which hinder their readiness for clinical application. They emphasize the need for future research to focus on prospective validation in diverse patient groups to enhance the clinical utility of these AI tools.