Martina Iammarino

Orcid: 0000-0001-8025-733X

According to our database¹, Martina Iammarino authored at least 37 papers between 2019 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2025

Process mining applications in healthcare: a systematic literature review.

[BibT_eX]

[DOI]

PeerJ Comput. Sci., 2025

What Time Is It? Finding Which Temporal Features is More Useful for Next Activity Prediction.

[BibT_eX]

[DOI]

IEEE Open J. Comput. Soc., 2025

2024

A systematic review on artificial intelligence approaches for smart health devices.

[BibT_eX]

[DOI]

PeerJ Comput. Sci., 2024

Raman Spectroscopy of Cancer Cells: An Explainable Classification Model.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2024

A Machine Learning Approach for the Detection of Thoracic Disease using Chest X-ray reports.

[BibT_eX]

[DOI]

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 28th International Conference KES-2024, 2024

Adopting Delta Maintainability Model for Just in Time Bug Prediction.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Software Technologies, 2024

2023

A data-aware explainable deep learning approach for next activity prediction.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., November, 2023

Evo-GUNet3++: Using evolutionary algorithms to train UNet-based architectures for efficient 3D lung cancer detection.

[BibT_eX]

[DOI]

Appl. Soft Comput., September, 2023

Forecasting technical debt evolution in software systems: an empirical study.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., 2023

Forecasting the Developer's Impact in Managing the Technical Debt.

[BibT_eX]

[DOI]

Proceedings of the Product-Focused Software Process Improvement, 2023

Raman Spectroscopy of Cells for Cancer Classification Through Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2023

Early Diagnosis of Parkinson's Disease Exploting Motor and Non-Motor Symptoms: Results from the PPMI Cohort.

[BibT_eX]

[DOI]

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 27th International Conference KES-2023, 2023

Understanding Compiler Effects on Clone Detection Process.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Software Technologies, 2023

Early Parkinson's Disease Detection from EEG Traces Using Machine Learning Techniques.

[BibT_eX]

[DOI]

Proceedings of the Fuzzy Logic and Technology, and Aggregation Operators, 2023

An Empirical Study on the Relationship Between the Co-Occurrence of Design Smell and Refactoring Activities.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering, 2023

An Explainable Approach for Early Parkinson Disease Detection Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Deep Learning Theory and Applications - 4th International Conference, 2023

Machine Learning Applied to Speech Recordings for Parkinson's Disease Recognition.

[BibT_eX]

[DOI]

Proceedings of the Deep Learning Theory and Applications - 4th International Conference, 2023

2022

Just-in-time software defect prediction using deep temporal convolutional networks.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2022

Using deep temporal convolutional networks to just-in-time forecast technical debt principal.

[BibT_eX]

[DOI]

J. Syst. Softw., 2022

Technical Debt Forecasting from Source Code Using Temporal Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the Product-Focused Software Process Improvement, 2022

An enhanced UNet variant for Effective Lung Cancer Detection.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Early Detection of Parkinson's Disease using Spiral Test and Echo State Networks.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Is There Any Correlation between Refactoring and Design Smell Occurrence?

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Software Technologies, 2022

An Empirical Study to Predict Student Performance Using Information of the Virtual Learning Environment.

[BibT_eX]

[DOI]

Proceedings of the Higher Education Learning Methodologies and Technologies Online, 2022

A Machine Learning approach for Early Detection of Parkinson's Disease Using acoustic traces.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent System, 2022

Using Machine Learning for early prediction of Heart Disease.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent System, 2022

Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Deep Learning Theory and Applications, 2022

2021

An empirical study on the co-occurrence between refactoring actions and Self-Admitted Technical Debt removal.

[BibT_eX]

[DOI]

Martina Iammarino

Fiorella Zampetti

Lerina Aversano

Massimiliano Di Penta

J. Syst. Softw., 2021

Temporal convolutional networks for just-in-time design smells prediction using fine-grained software metrics.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Thyroid Disease Treatment prediction with machine learning approaches.

[BibT_eX]

[DOI]

Immacolata Cristina Nettore

Chiara Verdone

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

Technical Debt predictive model through Temporal Convolutional Network.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

Transfer Learning for Just-in-Time Design Smells Prediction using Temporal Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 16th International Conference on Software Technologies, 2021

2020

An Empirical Study on the Evolution of Design Smells.

[BibT_eX]

[DOI]

Lerina Aversano

Umberto Carpenito

Martina Iammarino

Inf., 2020

On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures.

[BibT_eX]

[DOI]

Algorithms, 2020

A Topic Modeling Approach To Evaluate The Comments Consistency To Source Code.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Investigating on the Relationships between Design Smells Removals and Refactorings.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on Software Technologies, 2020

2019

Self-Admitted Technical Debt Removal and Refactoring Actions: Co-Occurrence or More?

[BibT_eX]

[DOI]

Martina Iammarino

Fiorella Zampetti

Lerina Aversano

Massimiliano Di Penta

Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution, 2019

Martina Iammarino

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...