Baumann S, Renker M, Schoepf UJ, et al. - The effect of gender differences in the diagnostic results of machine-learning coronary CT angiography (cCTA)-derived fractional flow reserve (CT-FFR_ML) for detecting lesion-specific ischemia was explored by researchers. Five centers in the MACHINE (Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr) registry recruited 351 patients (73.5% male) with 525 vessels. In both men and women, the diagnostic performance to evaluate lesion-specific ischemia was evaluated on a per-vessel basis. A total of 398 vessels in men and 127 vessels in women were involved. According to findings, machine-learning based CT-FFR performs equally for the detection of lesion-specific ischemia in men and women with superior diagnostic performance over cCTA alone.