Jurman, Giuseppe

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

Chicco, D., & Jurman, G. (2020) · BMC Genomics

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 6,143

The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

Chicco, D., Warrens, M. J., & Jurman, G. (2021) · PeerJ Computer Science

Advanced Statistical Methods and ModelsStatistical Methods and Applications

Cited by 5,380

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

Chicco, D., Tötsch, N., & Jurman, G. (2021) · BioData Mining

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 893

Repeatability of published microarray gene expression analyses

Ioannidis, J. P. A., Allison, D. B., Ball, C. A., Coulibaly, I., Cui, X., Culhane, A. C., Falchi, M., Furlanello, C., Game, L., Jurman, G., et al. (2009) · Nature Genetics

Gene expression and cancer classificationScientific Computing and Data Management

Cited by 551

The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

Wang, C., Gong, B., Bushel, P. R., Thierry-Mieg, J., Thierry-Mieg, D., Xu, J., Fang, H., Hong, H., Shen, J., Su, Z., et al. (2014) · Nature Biotechnology

Gene expression and cancer classificationGenomics and Phylogenetic Studies

Cited by 512

A Comparison of MCC and CEN Error Measures in Multi-Class Prediction

Jurman, G., Riccadonna, S., & Furlanello, C. (2012) · PLoS ONE

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 406

Generative AI mitigates representation bias and improves model fairness through synthetic health data

Marchesi, R., Micheletti, N., I-Hsien Kuo, N., Barbieri, S., Jurman, G., & Osmani, V. (2025) · PLOS Computational Biology

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 29