version 0.1.0

app.py

@@ -142,8 +142,8 @@ gr.Interface(predict, [age, female, race, elective, aweekend, zipinc_qrtl, hosp_
             prior_cabg, prior_icd, prior_mi, prior_pci, prior_ppm, prior_tia_stroke,
             pulmonary_circulation_disorder, smoker, valvular_disease, weight_loss,
             endovascular_tavr, transapical_tavr], 
-            'label',
+            'text',
             live=True,
             title = "Predicting In-Hospital Mortality After TAVR Using Preoperative Variables and Penalized Logistic Regression",
             description = "The app below utilizes the finalized logistic regression model with an l2 penalty based on the manuscript by Alhwiti et al. The manuscript will be submitted to JACC: Cardiovascular Interventions. The data used for model building is all TAVR procedures between 2012 and 2019 as reported in the HCUP NIS database. <br><br> The purpose of the app is to provide evidence-based clinical support for interventional cardiology. <br> <br> For instruction on how to use the app and the encoding required for the variables,  please see <b>XYZ: insert website link here</b>.",
-            css = 'https://bootswatch.com/5/journal/bootstrap.css').launch(debug = True);
+            css = 'https://bootswatch.com/5/journal/bootstrap.css').launch(debug = False);