Predicting Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012 1.0.0
(3,359 bytes)
function [B,th,w]=get_param_coeffs_by_name(partitle)
switch partitle
case 'SAPS'
B=[3.7951; -0.1281];
th=0.21;
w=.296;
case 'SAPS_2d'
B=[4.5163; 0.1751;-0.2294];
w=.3732;
th=.25;
case 'RecordID'
B=[0 1000000000000];
case 'Age'
B=[1 150];
case 'Gender'
B=[0 1];
case 'Height'
B=[140 210];
case 'ICUType'
B=[1 4];
case 'Weight'
B=[25 200];
case 'Albumin'
B=[1 5.5];
case 'ALP'
B=[0 1600];
w=0.21993;
th=0.19;
case 'ALP_diff'
B=[1.2673; 0.0014];
w=0.21993;
th=0.19;
case 'ALT'
B=[0 12000];
case 'AST'
B=[0 12000];
case 'Bilirubin'
B=[0 1000]; % etsi hyvät rajat
case 'BUN'
B=[0 180];
case 'BUN_2d'
B=[2.5578;-0.0248; 0.0380];
w= 0.3024;
th=0.18;
case 'Cholesterol'
B=[10 350];
case 'Creatinine'
B=[0 20];
case 'DiasABP'
B=[20 120];
case 'FiO2'
B=[0 1];
case 'GCS'
B =[ 0.4715; 0.1284];
th=0.2;
w=.2861;
case 'GCS_diff'
B=[ 1.7151; -0.2124];
th=0.17;
w=.2913;
case 'GCS_2d'
B=[ -0.5006; 0.2043; -0.2999];
th=0.26;
w=.375;
case 'Glucose'
B=[10 450];
case 'HCO3'
B=[5 50];
case 'HCT'
B=[15 55];
case 'HR'
B=[20 200];
case 'K'
B=[2 8];
case 'Lactate'
B=[0 15];
case 'Mg'
B=[0.5 4.5];
case 'MAP'
B=[20 220];
case 'MechVent'
B=[0 1];
case 'Na'
B=[100 180];
case 'NIDiasABP'
B=[20 110];
case 'NIMAP'
B=[20 220];
case 'NISysABP'
B=[20 220];
case 'PaCO2'
B=[0 100];
case 'PaCO2_2d'
B=[-0.2423; 0.0447;-0.0102];
w = 0.2719;
th = 0.2000;
case 'PaO2'
B=[0 500];
case 'pH'
B=[6 8];
case 'Platelets'
B=[0 1000];
case 'RespRate'
B=[10 40];
case 'SaO2'
B=[20 100];
case 'SysABP'
B=[10 200];
case 'Temp'
B=[15 40];
case 'TroponinI'
B=[0 50];
case 'TroponinT'
B=[0 25];
case 'Urine'
B=[0 8000];
case 'Urine_2d'
B=[0.6741; 0.0007; -0.0003];
w=0.3148;
th=0.22;
case 'WBC'
B=[0 100];
case 'WBC_2d'
B=[2.3988;-0.0444; 0.0552];
w=0.217;
th=0.16;
otherwise
disp(['unknown parameter:' title])
B=[];
end
end
%
% 'RecordID';
% 'Age';
% 'Gender';
% '';
% '';
% '';