1
-
3
of
3
results (0.56 seconds)
Sort By:
-
Using Interpretable Machine Learning Methods: An Application to Health Insurance Fraud Detection
conroysimberg.com/blog/insurance-fraud-costs-the-u-s-308-billion- annually/#:~:text=The%20Coalition%2 ... between the fraudulent and non- fraudulent cases. Table 1 IMBALANCE IN DATASET Fraud Non-Fraud Number ...- Date: Jan 2024
- Topics: Health & Disability; Health & Disability>Health insurance; Technology & Applications; Technology & Applications>Artificial intelligence & machine learning
-
A Patient Centric Approach to AI in Health Insurance
022-00594-w 2. Gier, Jaime, Missed appointments cost the U.S. healthcare system $150B each year (2017). https://www ... com/clinical-it/article/13008175/missed-appointments-cost- the-u s-healthcare-system-150b-each-year 3. Karen Van Nuys ...- Authors: Scott Damery
- Date: May 2024
- Competency: Results-Oriented Solutions
- Topics: Health & Disability; Health & Disability>Health insurance; Technology & Applications; Technology & Applications>Artificial intelligence & machine learning
-
Using Interpretable Machine Learning Methods: An Application to Health Insurance Fraud Detection
Using Interpretable Machine Learning Methods: An Application to Health Insurance ... Postgraduate in Actuarial Data Science, SSSIHL Sai Siddhanth S, Postgraduate in Actuarial Data Science, SSSIHL Abhiishek ...- Date: Jan 2024
- Competency: External Forces & Industry Knowledge
- Topics: Health & Disability; Health & Disability>Health insurance; Technology & Applications; Technology & Applications>Artificial intelligence & machine learning