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Demos
Fraud: Detection & Avoidance of Opioid Fraud
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Demo
Fraud: Detection & Avoidance of Opioid Fraud
Tags:
Fraud Detection
Life Sciences & Health Care
Graph Technology
Summary:
Learn how to predict and prevent fraud in the event of opioid abuse.
Fraud Segmentation
Care Plan Flagging
Relationship Graphing
Geographic & Time Series
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Demo
Fraud Toolkit in Medical Healthcare Claims
Medical Healthcare Claims
Machine Learning, Graph Technology, and Time Series Structure
View Connections to Risky Communities
Tweak Graph and Machine Learning Algorithms to Flag Identified Patterns
Demo
Airlines, Logistics, & Transport Optimization Toolkit
Optimization for Crew, Craft, & Location
View Vital KPIs
Example Airline Use Cases
No Sequel and Graph database in Combination with Optimization Algorithms
Demo
Network Analytics Toolkit
IoT Connection of Multiple Devices in Real Time
Forecast Complex Dependent Networks
Graph and Time Series Data Structures with Analytics Back-End
Running 'What If' Scenarios
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Related Content
Lightning Talk
Graph For Supply Chain
Data modeling
Distribution networks
Resource planning
Process optimization
Demo
Customer 360: Retail
Cross Sell / Up Sell
Recommendation
Customer Relationship
Marketing Campaign
Online Seminar
Global Graph Day Celebration with Neo4j
New ways to store and retrieve data
BI Connector for connectivity to Neo4j
Neo4j Graph Data Science Library
Increased scalability
Blog
Use Real-time Graph Technology to Detect and Prevent Fraud
Learn how Graph Technology can help to identify risk and fraud patterns in order to quickly respond.
CASE Study
Predictive Analytics for Kinsa Health
Can you predict and plan for the flu?
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