Giuseppe Jurman
Orcid: 0000-0002-2705-5728Affiliations:
- Fondazione Bruno Kessler, Trento, Italy
According to our database1,
Giuseppe Jurman
authored at least 67 papers
between 2003 and 2023.
Collaborative distances:
Collaborative distances:
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on zbmath.org
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on orcid.org
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Bibliography
2023
A statistical comparison between Matthews correlation coefficient (MCC), prevalence threshold, and Fowlkes-Mallows index.
J. Biomed. Informatics, August, 2023
BioData Min., January, 2023
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma.
BioData Min., January, 2023
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification.
BioData Min., January, 2023
BioData Min., January, 2023
Differential diagnosis of systemic lupus erythematosus and Sjögren's syndrome using machine learning and multi-omics data.
Comput. Biol. Medicine, 2023
2022
histolab: A Python library for reproducible Digital Pathology preprocessing with automated testing.
SoftwareX, December, 2022
Automatically detecting Crohn's disease and Ulcerative Colitis from endoscopic imaging.
BMC Medical Informatics Decis. Mak., 2022
An Invitation to Greater Use of Matthews Correlation Coefficient in Robotics and Artificial Intelligence.
Frontiers Robotics AI, 2022
The ABC recommendations for validation of supervised machine learning results in biomedical sciences.
Frontiers Big Data, 2022
Frontiers Bioinform., 2022
Mitigating Health Data Poverty: Generative Approaches versus Resampling for Time-series Clinical Data.
CoRR, 2022
Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning.
BioData Min., 2022
2021
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation.
PeerJ Comput. Sci., 2021
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation.
BioData Min., 2021
The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment.
IEEE Access, 2021
The Benefits of the Matthews Correlation Coefficient (MCC) Over the Diagnostic Odds Ratio (DOR) in Binary Classification Assessment.
IEEE Access, 2021
Arterial Disease Computational Prediction and Health Record Feature Ranking Among Patients Diagnosed With Inflammatory Bowel Disease.
IEEE Access, 2021
An Ensemble Learning Approach for Enhanced Classification of Patients With Hepatitis and Cirrhosis.
IEEE Access, 2021
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021
2020
Multilayer Flows in Molecular Networks Identify Biological Modules in the Human Proteome.
IEEE Trans. Netw. Sci. Eng., 2020
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.
BMC Medical Informatics Decis. Mak., 2020
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020
2019
Remote. Sens., 2019
PLoS Comput. Biol., 2019
CoRR, 2019
High Resolution Forecasting of Heat Waves impacts on Leaf Area Index by Multiscale Multitemporal Deep Learning.
CoRR, 2019
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2019
2018
Deep learning for automatic stereotypical motor movement detection using wearable sensors in autism spectrum disorders.
Signal Process., 2018
2017
A multiobjective deep learning approach for predictive classification in Neuroblastoma.
CoRR, 2017
2016
Efficient randomization of biological networks while preserving functional characterization of individual nodes.
BMC Bioinform., 2016
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016
2015
CoRR, 2015
Graph metrics as summary statistics for Approximate Bayesian Computation with application to network model parameter estimation.
J. Complex Networks, 2015
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015
2014
Entropy Dynamics of Community Alignment in the Italian Parliament Time-Dependent Network.
CoRR, 2014
Bioinform., 2014
2013
minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers.
Bioinform., 2013
2012
2011
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2011
2010
Int. J. Algebra Comput., 2010
A machine learning pipeline for quantitative phenotype prediction from genotype data.
BMC Bioinform., 2010
Proceedings of the Neural Nets WIRN10, 2010
2008
Int. J. Approx. Reason., 2008
Bioinform., 2008
2007
J. Integr. Bioinform., 2007
Proceedings of the Multiple Classifier Systems, 7th International Workshop, 2007
2006
IEEE Trans. Signal Process., 2006
Neural Networks, 2006
Proceedings of the 19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 2006
Proceedings of the 1st International ICST Conference on Bio Inspired Models of Network, 2006
2005
IEEE ACM Trans. Comput. Biol. Bioinform., 2005
Proceedings of the Fuzzy Logic and Applications, 6th International Workshop, 2005
Proceedings of the Image Analysis and Processing, 2005
2004
Proceedings of the Multiple Classifier Systems, 5th International Workshop, 2004
2003
Neural Networks, 2003
Entropy-based gene ranking without selection bias for the predictive classification of microarray data.
BMC Bioinform., 2003