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Fraud Prevention: Healthcare
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Demo
Fraud Prevention: Healthcare
Tags:
Fraud Detection
Life Sciences & Health Care
Graph Technology
Summary:
Claims Fraud
Risk Scoring
Opioid Segmentation
Fraud Intervention
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Fraud Detection and Prevention in Healthcare Claims
Challenges in payer and provider Fraud
Methods to reduce false positives by 10%
Increase accuracy of ID and intervention
Use of visualizations for explainable ML
Blog
The Three Paradigms of GraphML
The three types of graph machine learning (graphML) are smart data extraction, data structure analysis, and full graphML. This article explains all three.
CASE Study
Predictive Analytics for Kinsa Health
Can you predict and plan for the flu?
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