Richard A. Bauder

According to our database1, Richard A. Bauder authored at least 25 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Investigating the relationship between time and predictive model maintenance.
J. Big Data, 2020

Investigating class rarity in big data.
J. Big Data, 2020

A study on rare fraud predictions with big Medicare claims fraud data.
Intell. Data Anal., 2020

2019
The effects of class rarity on the evaluation of supervised healthcare fraud detection models.
J. Big Data, 2019

Severely imbalanced Big Data challenges: investigating data sampling approaches.
J. Big Data, 2019

Evaluating Model Predictive Performance: A Medicare Fraud Detection Case Study.
Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019

The Effect of Time on the Maintenance of a Predictive Model.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2018
Machine Learning Algorithms with Big Medicare Fraud Data.
PhD thesis, 2018

A survey on addressing high-class imbalance in big data.
J. Big Data, 2018

Big Data fraud detection using multiple medicare data sources.
J. Big Data, 2018

The effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data.
Health Inf. Sci. Syst., 2018

Identifying Medicare Provider Fraud with Unsupervised Machine Learning.
Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

Medicare Fraud Detection Using Random Forest with Class Imbalanced Big Data.
Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

A Survey of Medicare Data Processing and Integration for Fraud Detection.
Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

Data Sampling Approaches with Severely Imbalanced Big Data for Medicare Fraud Detection.
Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

An Empirical Study on Class Rarity in Big Data.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Fraud Detection with a Limited Number of Known Fraudulent Medicare Providers.
Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

The Detection of Medicare Fraud Using Machine Learning Methods with Excluded Provider Labels.
Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

2017
Medical Provider Specialty Predictions for the Detection of Anomalous Medicare Insurance Claims.
Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration, 2017

Estimating Outlier Score Probabilities.
Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration, 2017

Medicare Fraud Detection Using Machine Learning Methods.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Multivariate Anomaly Detection in Medicare using Model Residuals and Probabilistic Programming.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

2016
A Novel Method for Fraudulent Medicare Claims Detection from Expected Payment Deviations (Application Paper).
Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims.
Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016

A Probabilistic Programming Approach for Outlier Detection in Healthcare Claims.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016


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