| A survey on addressing high-class imbalance in big data JL Leevy, TM Khoshgoftaar, RA Bauder, N Seliya Journal of Big Data 5 (1), 1-30, 2018 | 650 | 2018 |
| Big data fraud detection using multiple medicare data sources M Herland, TM Khoshgoftaar, RA Bauder Journal of Big Data 5 (1), 1-21, 2018 | 174 | 2018 |
| A survey on the state of healthcare upcoding fraud analysis and detection RA Bauder, TM Khoshgoftaar, N Seliya HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY 17 (1), 31-55, 2017 | 120 | 2017 |
| Medicare fraud detection using machine learning methods RA Bauder, TM Khoshgoftaar 2017 16th IEEE international conference on machine learning and applications …, 2017 | 112 | 2017 |
| Severely imbalanced big data challenges: investigating data sampling approaches T Hasanin, TM Khoshgoftaar, JL Leevy, RA Bauder Journal of Big Data 6 (1), 1-25, 2019 | 94 | 2019 |
| The effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data RA Bauder, TM Khoshgoftaar Health information science and systems 6, 1-14, 2018 | 86 | 2018 |
| Medicare fraud detection using random forest with class imbalanced big data R Bauder, T Khoshgoftaar 2018 IEEE international conference on information reuse and integration (IRI …, 2018 | 79 | 2018 |
| Predicting medical provider specialties to detect anomalous insurance claims RA Bauder, TM Khoshgoftaar, A Richter, M Herland 2016 IEEE 28th international conference on tools with artificial …, 2016 | 73 | 2016 |
| A novel method for fraudulent medicare claims detection from expected payment deviations (application paper) RA Bauder, TM Khoshgoftaar 2016 IEEE 17th international conference on information reuse and integration …, 2016 | 64 | 2016 |
| The detection of medicare fraud using machine learning methods with excluded provider labels RA Bauder, TM Khoshgoftaar The Thirty-First International Flairs Conference, 2018 | 55 | 2018 |
| Data sampling approaches with severely imbalanced big data for medicare fraud detection RA Bauder, TM Khoshgoftaar, T Hasanin 2018 IEEE 30th international conference on tools with artificial …, 2018 | 54 | 2018 |
| Multivariate outlier detection in medicare claims payments applying probabilistic programming methods RA Bauder, TM Khoshgoftaar Health Services and Outcomes Research Methodology 17, 256-289, 2017 | 53 | 2017 |
| An empirical study on class rarity in big data RA Bauder, TM Khoshgoftaar, T Hasanin 2018 17th IEEE international conference on machine learning and applications …, 2018 | 52 | 2018 |
| A probabilistic programming approach for outlier detection in healthcare claims RA Bauder, TM Khoshgoftaar 2016 15th IEEE international conference on machine learning and applications …, 2016 | 52 | 2016 |
| Identifying medicare provider fraud with unsupervised machine learning R Bauder, R da Rosa, T Khoshgoftaar 2018 IEEE international conference on information Reuse and integration (IRI …, 2018 | 50 | 2018 |
| Medical provider specialty predictions for the detection of anomalous medicare insurance claims M Herland, RA Bauder, TM Khoshgoftaar 2017 IEEE international conference on information reuse and integration (IRI …, 2017 | 46 | 2017 |
| The effects of class rarity on the evaluation of supervised healthcare fraud detection models M Herland, RA Bauder, TM Khoshgoftaar Journal of Big Data 6, 1-33, 2019 | 44 | 2019 |
| Approaches for identifying US medicare fraud in provider claims data M Herland, RA Bauder, TM Khoshgoftaar Health care management science 23, 2-19, 2020 | 27 | 2020 |
| A survey of medicare data processing and integration for fraud detection R Bauder, T Khoshgoftaar 2018 IEEE international conference on information reuse and integration (IRI …, 2018 | 27 | 2018 |
| Investigating class rarity in big data T Hasanin, TM Khoshgoftaar, JL Leevy, RA Bauder Journal of Big Data 7, 1-17, 2020 | 23 | 2020 |
Taghi M. KhoshgoftaarMotorola Endowed Chair Professor, Computer Science, Florida Atlantic UniversityVerified email at fau.edu
