app.py

import gradio as gr
import pandas as pd
import re

def detect_fraud(provider, procedure, amount, notes):
    """
    Lightweight rule-based fraud indicator for demonstration.
    """

    text = f"{provider} {procedure} {notes}".lower()

    # Rule-based flags (common healthcare fraud patterns)
    upcoding_terms = ["complex visit", "level 5", "high severity", "multiple procedures"]
    phantom_terms = ["no patient", "patient denies", "never seen"]
    unbundling_terms = ["billed separately", "duplicate", "split billing"]
    high_amount_threshold = 5000  # simple flag

    flags = []

    # Fraud pattern detection
    if any(term in text for term in upcoding_terms):
        flags.append("Upcoding")

    if any(term in text for term in phantom_terms):
        flags.append("Phantom Billing")

    if any(term in text for term in unbundling_terms):
        flags.append("Unbundling")

    if amount > high_amount_threshold:
        flags.append("High-Dollar Flag")

    # Score logic
    if len(flags) >= 3:
        score = "High Fraud Risk"
    elif len(flags) == 2:
        score = "Moderate Fraud Risk"
    elif len(flags) == 1:
        score = "Low Fraud Risk"
    else:
        score = "No Fraud Indicators Found"

    df = pd.DataFrame({
        "Provider": [provider],
        "Procedure": [procedure],
        "Amount": [amount],
        "Detected Flags": [", ".join(flags) if flags else "None"],
        "Fraud Risk Score": [score]
    })

    return df, f"### Fraud Risk: **{score}**\nFlags: {', '.join(flags) if flags else 'None'}"

# ---- Gradio App UI ----

with gr.Blocks(title="Healthcare Fraud Detection Demo") as demo:
    gr.Markdown("## 🏥 Healthcare Fraud Detection – Demo (Rule-Based)")
    gr.Markdown("Upload simple claim information to evaluate possible fraud indicators.")

    with gr.Row():
        provider = gr.Textbox(label="Provider Name", placeholder="Example: ABC Clinic")
        procedure = gr.Textbox(label="Procedure Code/Description", placeholder="Example: Level 5 visit")

    amount = gr.Number(label="Claim Amount ($)", value=1200)

    notes = gr.Textbox(
        label="Claim Notes",
        lines=6,
        placeholder="Example: Patient denies visit. Procedure billed separately..."
    )

    submit = gr.Button("Analyze Claim")

    output_table = gr.Dataframe(label="Fraud Detection Summary")
    output_text = gr.Markdown(label="Fraud Score")

    submit.click(
        detect_fraud,
        inputs=[provider, procedure, amount, notes],
        outputs=[output_table, output_text]
    )

demo.launch(share=True)