Update app.py

app.py

@@ -14,27 +14,33 @@ model = joblib.load("typhoidguard_model_reduced.pkl")
 
 # Risk & Agent Logic
 # Risk & Agentic Logic
+
 def predict_and_generate(name, age, gender, platelets, hb, duration, calcium, potassium):
 
-    # 1️⃣ Prepare input DataFrame
+    # 1️⃣ Prepare data with exact column names
     data = pd.DataFrame([{
-    "Platelet Count": platelets,
-    "Age": age,
-    "Hemoglobin (g/dL)": hb,
-    "Treatment Duration": duration,
-    "Calcium (mg/dL)": calcium,
-    "Potassium (mmol/L)": potassium,
-    "Gender": gender
+        "Platelet Count": platelets,
+        "Age": age,
+        "Hemoglobin (g/dL)": hb,
+        "Treatment Duration": duration,
+        "Calcium (mg/dL)": calcium,
+        "Potassium (mmol/L)": potassium,
+        "Gender": gender
     }])
 
-    # 2️⃣ Pass data through preprocessor
+    # 2️⃣ Transform through preprocessor
     X_processed = model.named_steps["preprocessor"].transform(data)
 
-    # 3️⃣ Get probability from classifier
-    prob = model.named_steps["classifier"].predict_proba(X_processed)[0][1]  # probability of treatment failure
+    # 3️⃣ Model probability
+    prob = model.named_steps["classifier"].predict_proba(X_processed)[0][1]
     prob_pct = round(prob * 100, 2)
 
-    # 4️⃣ Risk label based on probability
+    # 4️⃣ Clinical thresholds (override)
+    low_platelets = platelets < 150000
+    low_hb = hb < 10
+    prolonged_treatment = duration > 7
+
+    # Default risk label based on probability
     if prob > 0.65:
         risk_label = "🔴 HIGH RISK"
         color = "#d62828"
@@ -45,38 +51,30 @@ def predict_and_generate(name, age, gender, platelets, hb, duration, calcium, po
         risk_label = "🟢 LOW RISK"
         color = "#2a9d8f"
 
-    # 5️⃣ Agentic triage logic (include critical thresholds)
-    patient_data = data.iloc[0].to_dict()
-    low_platelets = patient_data.get("Platelet Count", 999999) < 150000
-    low_hb = patient_data.get("Hemoglobin (g/dL)", 999) < 10
-
-    if prob > 0.65 or low_platelets or low_hb:
-        recommendation = "Immediate referral to secondary care facility recommended. Close monitoring required."
+    # Override risk for critical lab values
+    if low_platelets or low_hb:
         risk_label = "🔴 HIGH RISK"
         color = "#d62828"
-    elif 0.35 <= prob <= 0.65:
+        recommendation = "Immediate referral to secondary care facility recommended. Close monitoring required."
+    elif prob >= 0.35:
         recommendation = "Close monitoring advised. Repeat blood tests within 48 hours."
-        risk_label = "🟡 MODERATE RISK"
-        color = "#f4a261"
     else:
         recommendation = "Continue standard treatment protocol."
-        risk_label = "🟢 LOW RISK"
-        color = "#2a9d8f"
 
-    # 6️⃣ Top clinical factors
+    # 5️⃣ Risk factors list
     factors = []
     if low_platelets:
         factors.append("Low Platelet Count")
     if low_hb:
         factors.append("Low Hemoglobin")
-    if duration > 7:
+    if prolonged_treatment:
         factors.append("Prolonged Treatment Duration")
     if calcium < 8.5:
         factors.append("Low Calcium")
     if potassium < 3.5 or potassium > 5.0:
         factors.append("Abnormal Potassium")
 
-    # 7️⃣ Construct HTML
+    # 6️⃣ Construct HTML
     explanation = f"""
     <div style="font-family:Arial; padding:15px;">
         <h2 style="color:{color};">Patient: {name}</h2>
@@ -123,7 +121,7 @@ def generate_pdf(name, age, gender, platelets, hb, duration, calcium, potassium)
     elements.append(table)
     elements.append(Spacer(1, 0.5 * inch))
     elements.append(Paragraph("Generated under HEC Generative AI Training Hackathon", styles["Normal"]))
-    elements.append(Paragraph("Team Kohsar AI - AJK", styles["Normal"]))
+    elements.append(Paragraph("Team Chinar AI - AJK", styles["Normal"]))
 
     doc.build(elements)
     return file_path
@@ -135,7 +133,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
     # 🏥 TyphoidGuard AI
     ### HEC Generative AI Training Hackathon – Pakistan
-    #### Team Kohsar AI (AJK)
+    #### Team Chinar AI (AJK)
     """)
 
     with gr.Row():