AI Powered Healthcare Fraud Detection System

Описание: Discover how our AI-Powered Healthcare Fraud Detection System is revolutionizing fraud prevention in healthcare. Traditional methods are slow, reactive, and often miss critical unstructured data like doctor’s notes and insurance claims, leading to financial losses and operational inefficiencies.

Our system combines Hybrid Machine Learning, Generative AI, and IBM RAG to detect fraudulent claims intelligently and proactively. It cleans and analyzes structured and unstructured data, retrieves context from past cases and regulations, and generates clear, human-readable reports for auditors.

Key Features:

GenAI Explanations: Understand why a claim is flagged.

RAG-Enhanced Analysis: Reduces false positives with contextual retrieval.

Synthetic Data Generation: Strengthens model accuracy even with limited real-world examples.

Multi-Modal Detection: Detects complex fraud patterns across multiple data types.

Agentic AI: Automates workflow for efficient claim management.

Technology Stack: Python, Scikit-learn, XGBoost, PyTorch, ClinicalBERT, Mistral-7B, IBM RAG, FastAPI, Streamlit, and Docker.

Impact: Reduces financial losses, improves operational efficiency, protects patients, ensures fair billing, and builds trust in healthcare.

This video explains how integrating AI and RAG technologies creates a smarter, safer, and more transparent healthcare ecosystem.