Deep Learning and Thresholding with Class-Imbalanced Big Data. - Justin M. Johnson; Taghi M. Khoshgoftaar (ICMLA, 2019)

Deep Learning and Data Sampling with Imbalanced Big Data. - Justin M. Johnson; Taghi M. Khoshgoftaar (IRI, 2019)

Survey on deep learning with class imbalance. - Justin M. Johnson; Taghi M. Khoshgoftaar (J. Big Data, 2019)

Medicare fraud detection using neural networks. - Justin M. Johnson; Taghi M. Khoshgoftaar (J. Big Data, 2019)

Hcpcs2Vec: Healthcare Procedure Embeddings for Medicare Fraud Prediction. - Justin M. Johnson; Taghi M. Khoshgoftaar (CIC, 2020)

Semantic Embeddings for Medical Providers and Fraud Detection. - Justin M. Johnson; Taghi M. Khoshgoftaar (IRI, 2020)

The Effects of Data Sampling with Deep Learning and Highly Imbalanced Big Data. - Justin M. Johnson; Taghi M. Khoshgoftaar (Inf. Syst. Frontiers, 2020)

Robust Thresholding Strategies for Highly Imbalanced and Noisy Data. - Justin M. Johnson; Taghi M. Khoshgoftaar (ICMLA, 2021)

Output Thresholding for Ensemble Learners and Imbalanced Big Data. - Justin M. Johnson; Taghi M. Khoshgoftaar (ICTAI, 2021)

The Effects of Class Label Noise on Highly-Imbalanced Big Data. - Robert K. L. Kennedy; Justin M. Johnson; Taghi M. Khoshgoftaar (ICTAI, 2021)

Encoding Techniques for High-Cardinality Features and Ensemble Learners. - Justin M. Johnson; Taghi M. Khoshgoftaar (IRI, 2021)

Medical Provider Embeddings for Healthcare Fraud Detection. - Justin M. Johnson; Taghi M. Khoshgoftaar (SN Comput. Sci., 2021)

A Comparative Approach to Threshold Optimization for Classifying Imbalanced Data. - John T. Hancock; Justin M. Johnson; Taghi M. Khoshgoftaar (CIC, 2022)

Informative Evaluation Metrics for Highly Imbalanced Big Data Classification. - John T. Hancock; Taghi M. Khoshgoftaar; Justin M. Johnson (ICMLA, 2022)

Cost-Sensitive Ensemble Learning for Highly Imbalanced Classification. - Justin M. Johnson; Taghi M. Khoshgoftaar (ICMLA, 2022)

GANs for Class-Imbalanced Data: A Meta-Analysis of GitHub Projects. - Rick Sauber-Cole; Taghi M. Khoshgoftaar; Justin M. Johnson (ICTAI, 2022)

Healthcare Provider Summary Data for Fraud Classification. - Justin M. Johnson; Taghi M. Khoshgoftaar (IRI, 2022)

The Effects of Random Undersampling for Big Data Medicare Fraud Detection. - John T. Hancock; Taghi M. Khoshgoftaar; Justin M. Johnson (SOSE, 2022)

A Survey on Classifying Big Data with Label Noise. - Justin M. Johnson; Taghi M. Khoshgoftaar (ACM J. Data Inf. Qual., 2022)

Encoding High-Dimensional Procedure Codes for Healthcare Fraud Detection. - Justin M. Johnson; Taghi M. Khoshgoftaar (SN Comput. Sci., 2022)

Data-Centric AI for Healthcare Fraud Detection. - Justin M. Johnson; Taghi M. Khoshgoftaar (SN Comput. Sci., 2023)

Learning from Highly Imbalanced Big Data with Label Noise. - Justin M. Johnson; Robert K. L. Kennedy; Taghi M. Khoshgoftaar (Int. J. Artif. Intell. Tools, 2023)

Evaluating classifier performance with highly imbalanced Big Data. - John T. Hancock; Taghi M. Khoshgoftaar; Justin M. Johnson (J. Big Data, 2023)

Threshold optimization and random undersampling for imbalanced credit card data. - Joffrey L. Leevy; Justin M. Johnson; John T. Hancock; Taghi M. Khoshgoftaar (J. Big Data, 2023)