Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 1.0.2
(717 bytes)
E09442 12 500 5000
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -68 -12832 0 I
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -68 -29303 0 II
E09442.mat 16x1+24 1000.0(0)/mV 16 0 0 -15907 0 III
E09442.mat 16x1+24 1000.0(0)/mV 16 0 68 21484 0 aVR
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -34 1639 0 aVL
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -34 -22564 0 aVF
E09442.mat 16x1+24 1000.0(0)/mV 16 0 19 21171 0 V1
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -370 27725 0 V2
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -117 -22020 0 V3
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -97 -3911 0 V4
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -97 -18873 0 V5
E09442.mat 16x1+24 1000.0(0)/mV 16 0 -97 27318 0 V6
# Age: 79
# Sex: Female
# Dx: 164873001
# Rx: Unknown
# Hx: Unknown