Patient 360 + Opioid Fraud Detection Using Machine Learning and TigerGraph
April 26, 2019
More Online Seminars
What You Will Learn
- Full Patient 360 - Tie all aspects of the patient together and identify relationships. Use Graph & Time Series to view history and identify with ML patterns.
- Churn Prevention - Data segmentation, analytics for historical data and pattern views.
- Sentiment Tracking & Patient Care Analysis - Analytics to navigate your data and track patient care.
- Identification of Claim Anomalies - Fast, impactful analysis of data for anomaly detection.
- Member Care & Doctor Abuse Detection - Intervention and Graph relationship management for cause and case tracking.
- Influence Analysis - Most influential doctors + pharmacies; most influential financial analysts.
- Network Efficiency - Using graph to determine which networks are most efficient.
- Working Prototypes - See graph and ML in action