Match terminology

niivue · Jun 11, 2024 · 6dc6874 · 6dc6874
1 parent bc86da6
commit 6dc6874
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/main.js b/main.js
@@ -61,11 +61,11 @@ async function main() {
         PC[p] = norm0to1(PC[p], -51.9073, 110.0535)
     }
     let acuteCoC = parseFloat(cocNumber.value)
-    acuteCoC = norm0to1(acuteCoC, -0.024243014, 0.951938077)
+    let acuteCoC0_1 = norm0to1(acuteCoC, -0.024243014, 0.951938077)
     let lesionVolTotalML = lesionVolTotal / 1000
     let ROI_volML = lesionVol / 1000
     let ROI_vol0_1 = norm0to1(ROI_volML, 0, 21.625)
-    const input_vector = [PC[0], PC[1], PC[2], PC[3], PC[4], acuteCoC, ROI_vol0_1]
+    const input_vector = [PC[0], PC[1], PC[2], PC[3], PC[4], acuteCoC0_1, ROI_vol0_1]
     // console.log(input_vector)
     let prediction_sum = 0
     for (let m = 0; m < models.length; m++) {
@@ -121,7 +121,7 @@ async function main() {
   }
   predictBtn.onclick = function () {
     const [acuteCoC, acuteZ, lesionVolTotalML, ROI_volML, chronCoC, chronZ] = neglect_predict()
-    const str = (`Given ${lesionVolTotalML}ml lesion (with ${ROI_volML} in core neglect voxels), and acute CoC ${acuteCoC}  (z= ${acuteZ}), predicted chronic CoC is ${chronCoC} (z= ${chronZ})`)
+    const str = (`Given ${lesionVolTotalML.toFixed(4)}ml lesion (with ${ROI_volML.toFixed(4)} in core neglect voxels), and acute CoC ${acuteCoC.toFixed(2)}  (z= ${acuteZ.toFixed(4)}), predicted chronic CoC is ${chronCoC.toFixed(2)} (z= ${chronZ.toFixed(4)})`)
     window.alert(str)
   }
   aboutBtn.onclick = function () {

diff --git a/public/neglect_predict.m b/public/neglect_predict.m
@@ -58,11 +58,11 @@ function neglect_predict(fnm, acuteCoC)
     for i = 1:5
         PC(i) = norm0to1(PC(i), -51.9073, 110.0535);
     end
-   acuteCoC = norm0to1(acuteCoC, -0.024243014, 0.951938077);
-    ROI_volML = norm0to1(ROI_volML, 0, 21.625);
+    acuteCoC01 = norm0to1(acuteCoC, -0.024243014, 0.951938077);
+    ROI_volML01 = norm0to1(ROI_volML, 0, 21.625);
     % input_vector = [PC1, PC2, PC3, PC4, PC5, CoC, ROI_vol];
     % Exemplary patient data (with outcome = 0.8155):
-    input_vector = [PC(1), PC(2), PC(3), PC(4), PC(5), acuteCoC, ROI_volML];
+    input_vector = [PC(1), PC(2), PC(3), PC(4), PC(5), acuteCoC01, ROI_volML01];
     fnmModel = fullfile(mpath, 'models_5x10_diff.mat');
     if ~exist(fnmPCA,'file')
         error('Unable to find %s', fnmPCA)