Anomaly detection: 4 AI-based approaches

Fraud Detection in Healthcare: a step-by-step guide to incorporating machine learning

Cover

Healthcare practices and operations must face life-and-death challenges every day, and for best performance organizations need to minimize waste, yet fraudsters cost healthcare providers billions of dollars a year.

Current fraud detection methods often rely on broad-strokes predictions or brute force human analysis.

Make the shift to machine learning-based models with this guidebook, which includes:
- A broader overview of the role of anomaly detection in healthcare (beyond fraud detection) and ways to integrate the process into existing workflows.
- Code samples for a simple machine learning-based stock optimization model, along with ways to customize and improve it.
- How to approach ROI calculations when determining the first steps towards machine learning integration.

Vendor:
Dataiku
Posted:
14 Jan 2020
Published:
14 Jan 2020
Format:
PDF
Length:
20 Page(s)
Type:
eGuide
Language:
English
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