Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 1.0.2
(724 bytes)
E09112 12 500 5000
E09112.mat 16x1+24 1000.0(0)/mV 16 0 87 -7156 0 I
E09112.mat 16x1+24 1000.0(0)/mV 16 0 43 -3060 0 II
E09112.mat 16x1+24 1000.0(0)/mV 16 0 -43 3899 0 III
E09112.mat 16x1+24 1000.0(0)/mV 16 0 -65 -27720 0 aVR
E09112.mat 16x1+24 1000.0(0)/mV 16 0 65 27335 0 aVL
E09112.mat 16x1+24 1000.0(0)/mV 16 0 0 645 0 aVF
E09112.mat 16x1+24 1000.0(0)/mV 16 0 -43 -21615 0 V1
E09112.mat 16x1+24 1000.0(0)/mV 16 0 0 26300 0 V2
E09112.mat 16x1+24 1000.0(0)/mV 16 0 234 -21487 0 V3
E09112.mat 16x1+24 1000.0(0)/mV 16 0 -112 32580 0 V4
E09112.mat 16x1+24 1000.0(0)/mV 16 0 -97 -6988 0 V5
E09112.mat 16x1+24 1000.0(0)/mV 16 0 48 29302 0 V6
# Age: 75
# Sex: Male
# Dx: 713426002,39732003,164934002
# Rx: Unknown
# Hx: Unknown