Predicting Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012 1.0.0

function [risk,prediction]=physionet2012(tm,category,val)
truncated=0;
inputs={'tm','category','val','truncated'};
SAPS={{'Age'},{'HR'},{'SysABP'},{'Temp'},...
    {'RespRate'},{'Urine'},{'BUN'},{'HCT'},...
    {'WBC'},{'Glucose'},{'K'},{'Na'},{'HCO3'},{'GCS'},...
    {'DiasABP'},{'Mg'},...
    {'PaCO2'},{'PaO2'},{'pH'},{'SaO2'},...
    };

tm=cell2mat(tm);
fr_data=find(str2num(tm(:,1:2))<48);
val=val(fr_data);
tm=str2num(tm(:,1:2));
tm=tm(fr_data);
category=category(fr_data);

count=0;
for s=1:length(SAPS)
    saps_var=SAPS{s};
    sig_ind= val.*0;
    for ii=1:length(saps_var)
        sig_ind=sig_ind | strcmp(saps_var(ii),category);
    end
    tmp_data=val(sig_ind);
    tmp_time=tm(sig_ind);
    mn=(tmp_data);
    eval(['temp_data =' saps_var{1} '(mn);'])
    [B, IX] = sort(tmp_time, 1);
    parameter(: , 1) = B;
    parameter(: , 2) = temp_data(IX(: , 1));
    
    temp=NaN*ones(1,48);
    for ii=1:48
        temp(1,ii) = mean(parameter(find( parameter(:,1)==(ii-1)),2));
    end
    
    tmp=NaN*ones(1,48);
    for ii=1:48
        tmp(1,ii) = mean(parameter(find( parameter(:,1)==(ii-1)),1));
    end
    
    x=find(isnan(temp)~=1);
    t=tmp(find(isnan(temp)~=1));
    y=temp(find(isnan(temp)~=1));
    xi=find(isnan(temp)==1);
    if length(t)==1
        temp=y*ones(1,48);
        tmp=0:47;
    elseif length(t)==0
        count=count+1;
        temp=0*ones(1,48);
        tmp=0:47;
    else
        new_tmp = interp1(x,t,xi,'linear','extrap');
        new_temp = interp1(x,y,xi,'linear');
        temp(xi)=new_temp;
        tmp(xi)=new_tmp;
    end
    
    x=find(isnan(temp)~=1);
    t=tmp(find(isnan(temp)~=1));
    y=temp(find(isnan(temp)~=1));
    xi=find(isnan(temp)==1);
    temp(xi(find(xi<x(1))))=temp(x(1));
    temp(xi(find(xi>x(end))))=temp(x(end));
    clear x t y xi
    
    tempdata(s,:) = temp;
    tmptime(s,:) = tmp;
    
    clear   temp1 temp tmp
    clear parameter
    
end

param=sum(tempdata);
time=sum(tmptime);
clear tempdata
clear tmptime



%% 
load net3
load minp
load maxp

param = 2*(param'-minp)./(maxp-minp) - 1;
CC = sim(net3 , param);

CC = CC';
[mx , ind] = max (CC);
prediction = ind-1;
risk = CC(: , 2);
if risk >0.5
    risk=((.99-.5)/(1-.5)).*(risk-.5)+.5;
elseif risk<.5
    risk=((.5-.01)/(.5-0)).*(risk)+.01;
end