Detection of Patients with Congenital and Often Concealed Long-QT Syndrome by Novel Deep Learning Models.
Florian DoldiLucas PlagwitzLea Philine HoffmannBenjamin RathGerrit FrommeyerFlorian ReinkePatrick LeitzAntonius BüscherFatih GünerTobias Johannes BrixFelix Konrad WegnerKevin WillyYvonne HanelSven DittmannWilhelm HaverkampEric Schulze-BahrJulian VargheseLars EckardtPublished in: Journal of personalized medicine (2022)
In this study, the XceptionTime model outperformed the FCN model for LQTS patients with even better results than in prior studies. Even when a patient cohort with cardiovascular comorbidities is used. AI-based ECG analysis is a promising step for correct LQTS patient identification, especially if common diagnostic measures might be misleading.