added report download feature

app.py

@@ -96,19 +96,69 @@ def process_img(img, brain_slice):
         
     return brain, fig, update_slider, gr.update(visible=True)
 
-def get_diagnosis(brain_img, age, MMSE, GDSCALE, CDR, FAQ, NPI, sex):
+def save_file(input_name, input_age, input_phone_num, input_emer_name, input_emer_phone_num,
+              input_sex, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, input_Diastolic_blood_pressure,
+              input_Systolic_blood_pressure, input_Body_heigth, input_Body_weight, input_Heart_rate,
+              input_Respiratory_rate, input_Body_temperature, input_Pluse_oximetry,
+              input_medications, input_allergies,diagnosis):
+    
+    
+    with open('results.txt', 'w') as f:
+            # Save Patient Data
+            f.write("Patient data:\n")
+            f.write(f"\tName: {input_name.capitalize()}\n")
+            f.write(f"\tSex: {input_sex}\n")
+            f.write(f"\tAge: {input_age}\n")
+            f.write(f"\tPhone Number: {input_phone_num}\n")
+            f.write(f"\tEmergency Contact Name: {input_emer_name.capitalize()}\n")
+            f.write(f"\tEmergency Contact Phone Number: {input_emer_phone_num}\n\n")
+    
+            # Save Vital Signs
+            f.write("Vital Signs:\n")
+            f.write(f"\tDiastolic blood pressure: {input_Diastolic_blood_pressure} mm Hg\n")
+            f.write(f"\tSystolic blood pressure: {input_Systolic_blood_pressure} mm Hg\n")
+            f.write(f"\tBody height: {input_Body_heigth} cm\n")
+            f.write(f"\tBody weight: {input_Body_weight} kg\n")
+            f.write(f"\tHeart rate: {input_Heart_rate} bpm\n")
+            f.write(f"\tRespiratory rate: {input_Respiratory_rate} bpm\n")
+            f.write(f"\tBody temperature: {input_Body_temperature} °C\n")
+            f.write(f"\tPulse oximetry: {input_Pluse_oximetry}%\n\n")
+    
+            # Save Medications
+            f.write("Medications:\n")
+            f.write(f"\tMedications: {input_medications}\n")
+            f.write(f"\tAllergies: {input_allergies}\n\n")
+            
+            # Save clinical data
+            f.write("Clinical data:\n")
+            f.write(f"\tMMSE total score: {input_MMSE}\n")
+            f.write(f"\tGDSCALE total score: {input_GDSCALE}\n")
+            f.write(f"\tGlobal CDR: {input_CDR}\n")
+            f.write(f"\tFAQ total score: {input_FAQ}\n")
+            f.write(f"\tNPI-Q total score: {input_NPI_Q}\n")
+                
+            # Save Diagnosis
+            f.write("Diagnosis:\n")
+            f.write(f"\t{diagnosis}\n")
+
+def get_diagnosis(brain_img, input_name, input_age, input_phone_num, input_emer_name, input_emer_phone_num,
+                  input_sex, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, input_Diastolic_blood_pressure,
+                  input_Systolic_blood_pressure, input_Body_heigth, input_Body_weight, input_Heart_rate,
+                  input_Respiratory_rate, input_Body_temperature, input_Pluse_oximetry,
+                  input_medications, input_allergies):
+    
     # Extracción de características de imagen
     features = utils.get_features(brain_img, mednet_model)
     
     # Clasificación de imagen
     label_img = np.array([svm_model.predict(features)])
     
-    if sex == "Male":
+    if input_sex == "Male":
         sex_dum = 1
     else:
         sex_dum = 0
     
-    scores = np.array([age, MMSE, GDSCALE, CDR, FAQ, NPI, sex_dum, label_img])
+    scores = np.array([input_age, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, sex_dum, label_img])
     
     print(scores)
     
@@ -123,12 +173,19 @@ def get_diagnosis(brain_img, age, MMSE, GDSCALE, CDR, FAQ, NPI, sex):
     
     # Probabilidad de tener MCI
     print(prob)
-    diagnosis = f"The patient has a probability of {(100*prob):.2f}%  of having MCI"
+    diagnosis = f"The patient has a probability of {(100*prob):.2f}% of having MCI"
+    
+    save_file(input_name, input_age, input_phone_num, input_emer_name, input_emer_phone_num,
+                  input_sex, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, input_Diastolic_blood_pressure,
+                  input_Systolic_blood_pressure, input_Body_heigth, input_Body_weight, input_Heart_rate,
+                  input_Respiratory_rate, input_Body_temperature, input_Pluse_oximetry,
+                  input_medications, input_allergies,diagnosis)
     
-    return gr.update(value=diagnosis)
+    return gr.update(value=diagnosis), gr.update(value="results.txt", visible=True), gr.update(visible=True)
+
 
 def clear():
-    return gr.File.update(value=None), gr.Plot.update(value=None), gr.update(visible=False), gr.Plot.update(value=None), gr.update(visible=False), gr.update(value="The diagnosis will show here..."), gr.update(visible=False), gr.update(visible=False)
+    return gr.File.update(value=None), gr.Plot.update(value=None), gr.update(visible=False), gr.Plot.update(value=None), gr.update(visible=False), gr.update(value="The diagnosis will show here..."), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
 
 '''--------------------------------- Interfaz ---------------------------------'''
@@ -200,8 +257,10 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
             with gr.Tab("Medications"):
                 input_medications = gr.Textbox(label='Medications', lines=5)
                 input_allergies = gr.Textbox(label='Allergies', lines=5)
-             
-            input_file = gr.File(file_count="single", label="MRI Image File (.nii)")
+                
+            with gr.Box():
+                gr.Markdown('<h4 style="color:#235784;">Upload MRI</h4>')             
+                input_file = gr.File(file_count="single", label="MRI File (.nii)", file_types=[".nii"], show_label=False)
             
             with gr.Row():
                 # Botón para cargar imagen
@@ -215,6 +274,11 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
             
             # Botón para obtener diagnostico
             diagnostic_button = gr.Button(value="Get diagnosis", visible=False, variant="primary")
+            
+            with gr.Box(visible=False) as download_box:
+                gr.Markdown('<h4 style="color:#235784;"> Dowload diagnosis report</h4>')  
+                # Descarga de archivo
+                output_file = gr.File(file_count="single", show_label=False, interactive=False, visible=True)
     
         # Outputs 
         with gr.Column(variant="panel", scale=1):
@@ -292,12 +356,16 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
     
     # Actualizar diagnostico
     diagnostic_button.click(fn=get_diagnosis, 
-                            inputs=[brain_img, input_age, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, input_sex],
-                            outputs=[diagnosis_text])
+                            inputs=[brain_img, input_name, input_age, input_phone_num, input_emer_name, input_emer_phone_num,
+                                    input_sex, input_MMSE, input_GDSCALE, input_CDR, input_FAQ, input_NPI_Q, input_Diastolic_blood_pressure,
+                                    input_Systolic_blood_pressure, input_Body_heigth, input_Body_weight, input_Heart_rate,
+                                    input_Respiratory_rate, input_Body_temperature, input_Pluse_oximetry,
+                                    input_medications, input_allergies],
+                            outputs=[diagnosis_text, output_file, download_box])
     
     # Limpiar campos
     clear_button.click(fn=clear, 
-                       outputs=[input_file, plot_img_original, mri_slider, plot_brain, brain_slider, diagnosis_text, process_button, diagnostic_button])
+                       outputs=[input_file, plot_img_original, mri_slider, plot_brain, brain_slider, diagnosis_text, process_button, diagnostic_button, download_box])