Performance of CatBoost and XGBoost in Medicare Fraud Detection

2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) ◽

10.1109/icmla51294.2020.00095 ◽

2020 ◽

Author(s):

John Hancock ◽

Taghi M. Khoshgoftaar

Keyword(s):

Fraud Detection ◽

Medicare Fraud

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Gradient Boosted Decision Tree Algorithms for Medicare Fraud Detection

SN Computer Science ◽

10.1007/s42979-021-00655-z ◽

2021 ◽

Vol 2 (4) ◽

Author(s):

John T. Hancock ◽

Taghi M. Khoshgoftaar

Keyword(s):

Decision Tree ◽

Fraud Detection ◽

Medicare Fraud ◽

Boosted Decision Tree ◽

Tree Algorithms

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Data Sampling Approaches with Severely Imbalanced Big Data for Medicare Fraud Detection

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) ◽

10.1109/ictai.2018.00030 ◽

2018 ◽

Cited By ~ 8

Author(s):

Richard A Bauder ◽

Taghi M Khoshgoftaar ◽

Tawfiq Hasanin

Keyword(s):

Big Data ◽

Fraud Detection ◽

Data Sampling ◽

Medicare Fraud

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The effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data

Health Information Science and Systems ◽

10.1007/s13755-018-0051-3 ◽

2018 ◽

Vol 6 (1) ◽

Cited By ~ 11

Author(s):

Richard A. Bauder ◽

Taghi M. Khoshgoftaar

Keyword(s):

Big Data ◽

Fraud Detection ◽

Medicare Fraud ◽

Class Distribution

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Medicare Fraud Detection Using Machine Learning Methods

2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA) ◽

10.1109/icmla.2017.00-48 ◽

2017 ◽

Cited By ~ 18

Author(s):

Richard A. Bauder ◽

Taghi M. Khoshgoftaar

Keyword(s):

Machine Learning ◽

Fraud Detection ◽

Learning Methods ◽

Medicare Fraud ◽

Machine Learning Methods

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Medicare Fraud Detection Using Random Forest with Class Imbalanced Big Data

2018 IEEE International Conference on Information Reuse and Integration (IRI) ◽

10.1109/iri.2018.00019 ◽

2018 ◽

Cited By ~ 12

Author(s):

Richard Bauder ◽

Taghi Khoshgoftaar

Keyword(s):

Big Data ◽

Random Forest ◽

Fraud Detection ◽

Medicare Fraud

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Medicare Fraud Detection using CatBoost

2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI) ◽

10.1109/iri49571.2020.00022 ◽

2020 ◽

Author(s):

John Hancock ◽

Taghi M. Khoshgoftaar

Keyword(s):

Fraud Detection ◽

Medicare Fraud

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Big Data and Class Imbalance in Medicare Fraud Detection

Reuse in Intelligent Systems ◽

10.1201/9781003034971-3 ◽

2020 ◽

pp. 62-86

Author(s):

Richard A Bauder ◽

Taghi M Khoshgoftaar

Keyword(s):

Big Data ◽

Class Imbalance ◽

Fraud Detection ◽

Medicare Fraud

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Machine learning and the future of Medicare fraud detection

Journal of the American Academy of Dermatology ◽

10.1016/j.jaad.2020.03.059 ◽

2020 ◽

Vol 83 (2) ◽

pp. e133

Author(s):

Dan Gordon ◽

Daniel M. Siegel

Keyword(s):

Machine Learning ◽

Fraud Detection ◽

Medicare Fraud ◽

The Future

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Evaluating Model Predictive Performance: A Medicare Fraud Detection Case Study

2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI) ◽

10.1109/iri.2019.00016 ◽

2019 ◽

Cited By ~ 2

Author(s):

Richard A. Bauder ◽

Matthew Herland ◽

Taghi M. Khoshgoftaar

Keyword(s):

Fraud Detection ◽

Predictive Performance ◽

Medicare Fraud

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An Anomaly Detection Method for Medicare Fraud Detection

2017 IEEE International Conference on Big Knowledge (ICBK) ◽

10.1109/icbk.2017.47 ◽

2017 ◽

Cited By ~ 1

Author(s):

Weijia Zhang ◽

Xiaofeng He

Keyword(s):

Anomaly Detection ◽

Detection Method ◽

Fraud Detection ◽

Medicare Fraud

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