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An innovative framework introduced by Santhosh Kumar Pendyala leverages AI and machine learning to tackle the complex issue of pricing opacity in the U.S. healthcare system. This approach aims to enhance transparency, optimize operations, and empower stakeholders by integrating diverse datasets for accurate cost predictions. The framework has shown significant improvements in billing consistency and operational efficiency across healthcare facilities.
The system utilizes advanced machine learning models like XGBoost and ARIMA, achieving a remarkable 92% prediction accuracy. Real-world applications have demonstrated an 85% reduction in pricing variability and a substantial increase in patient satisfaction, showcasing the potential of AI to transform healthcare pricing dynamics.
• AI framework enhances transparency in U.S. healthcare pricing.
• Machine learning models achieve 92% prediction accuracy in cost forecasting.
AI is utilized to analyze complex healthcare pricing data and improve transparency.
ML models like XGBoost and ARIMA are employed for accurate cost predictions.
Federated learning ensures data privacy while enabling collaborative analytics across healthcare facilities.
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