Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 1.0.2
(719 bytes)
E09315 12 500 5000
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -19 -30571 0 I
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -9 -8600 0 II
E09315.mat 16x1+24 1000.0(0)/mV 16 0 9 22175 0 III
E09315.mat 16x1+24 1000.0(0)/mV 16 0 14 19531 0 aVR
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -14 -26225 0 aVL
E09315.mat 16x1+24 1000.0(0)/mV 16 0 0 6689 0 aVF
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -39 21619 0 V1
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -156 -27867 0 V2
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -9 -22129 0 V3
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -97 -30107 0 V4
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -19 1563 0 V5
E09315.mat 16x1+24 1000.0(0)/mV 16 0 -39 28888 0 V6
# Age: 70
# Sex: Male
# Dx: 270492004,426177001
# Rx: Unknown
# Hx: Unknown