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import gradio as gr |
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import pandas as pd |
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def predict_benefit(plan_type, drug_tier, member_age): |
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""" |
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Simple demo logic: mock Drug Benefit Management score calculator. |
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Replace this with your model or logic. |
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""" |
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base_cost = 100 |
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tier_factor = {"Tier 1": 0.8, "Tier 2": 1.0, "Tier 3": 1.3}.get(drug_tier, 1.0) |
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plan_factor = {"Basic": 1.1, "Standard": 1.0, "Premium": 0.9}.get(plan_type, 1.0) |
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age_factor = 1.2 if member_age > 65 else 1.0 |
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total_cost = base_cost * tier_factor * plan_factor * age_factor |
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benefit_score = round(100 - total_cost / 2, 2) |
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return f"Estimated Benefit Score: {benefit_score}" |
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with gr.Blocks(title="Drug Benefit Management") as demo: |
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gr.Markdown("## 💊 Drug Benefit Management Model") |
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plan_type = gr.Dropdown(["Basic", "Standard", "Premium"], label="Plan Type") |
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drug_tier = gr.Dropdown(["Tier 1", "Tier 2", "Tier 3"], label="Drug Tier") |
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member_age = gr.Slider(18, 90, 45, label="Member Age") |
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output = gr.Textbox(label="Predicted Benefit Score") |
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submit = gr.Button("Calculate Benefit") |
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submit.click(predict_benefit, [plan_type, drug_tier, member_age], output) |
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demo.launch(share=True) |
