Maria Cuzzola

Orcid: 0000-0001-8749-5402

According to our database1, Maria Cuzzola authored at least 11 papers between 2009 and 2015.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2015
Comparative study of existing personalized approaches for identifying important gene markers and for risk estimation in Type2 Diabetes in Italian population.
Evol. Syst., 2015

2011
Personalized Modelling based Medical Decision Support System over Gene Expression Data: A New Framework Proposed.
Proceedings of the Neural Nets WIRN11, 2011

Knowledge Discovery and Risk Prediction for Chronic Diseases: An Integrated Approach.
Proceedings of the Engineering Applications of Neural Networks, 2011

Incremental - Adaptive - Knowledge Based - Learning for Informative Rules Extraction in Classification Analysis of aGvHD.
Proceedings of the Engineering Applications of Neural Networks, 2011

2010
Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis: A Computational Framework Proposed.
Aust. J. Intell. Inf. Process. Syst., 2010

Machine Learning and Personalized Modeling for Diagnosis of Acute GvHD: an Integrated Approach.
Proceedings of the Neural Nets WIRN10, 2010

Machine Learning and Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

2009
Computational Intelligence Methods for Discovering Diagnostic Gene Targets about aGVHD.
Proceedings of the Neural Nets WIRN09, 2009

Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach.
Proceedings of the Neural Information Processing, 16th International Conference, 2009

Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data.
Proceedings of the Artificial Neural Networks, 2009

A neural network model for early diagnosis of acute GVHD based on gene expression data.
Proceedings of the 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, 2009


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