Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 1.0.2
(716 bytes)
E09282 12 500 5000
E09282.mat 16x1+24 1000.0(0)/mV 16 0 0 -11425 0 I
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -92 10398 0 II
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -92 22710 0 III
E09282.mat 16x1+24 1000.0(0)/mV 16 0 46 401 0 aVR
E09282.mat 16x1+24 1000.0(0)/mV 16 0 46 -17426 0 aVL
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -92 16533 0 aVF
E09282.mat 16x1+24 1000.0(0)/mV 16 0 48 -21950 0 V1
E09282.mat 16x1+24 1000.0(0)/mV 16 0 14 4374 0 V2
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -87 -6239 0 V3
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -122 7933 0 V4
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -102 -5064 0 V5
E09282.mat 16x1+24 1000.0(0)/mV 16 0 -58 1144 0 V6
# Age: 50
# Sex: Male
# Dx: 164884008,195042002
# Rx: Unknown
# Hx: Unknown