Self-Admitted Technical Debt Removal and Refactoring Actions: Co-Occurrence or More? - Martina Iammarino; Fiorella Zampetti; Lerina Aversano; Massimiliano Di Penta (ICSME, 2019)

Investigating on the Relationships between Design Smells Removals and Refactorings. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Kateryna Romanyuk (ICSOFT, 2020)

A Topic Modeling Approach To Evaluate The Comments Consistency To Source Code. - Martina Iammarino; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (IJCNN, 2020)

On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures. - Lerina Aversano; Martina Iammarino; Mimmo Carapella; Andrea Del Vecchio; Laura Nardi (Algorithms, 2020)

An Empirical Study on the Evolution of Design Smells. - Lerina Aversano; Umberto Carpenito; Martina Iammarino (Inf., 2020)

Transfer Learning for Just-in-Time Design Smells Prediction using Temporal Convolutional Networks. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (ICSOFT, 2021)

Technical Debt predictive model through Temporal Convolutional Network. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (IJCNN, 2021)

Thyroid Disease Treatment prediction with machine learning approaches. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Paolo Emidio Macchia; Immacolata Cristina Nettore; Chiara Verdone (KES, 2021)

Temporal convolutional networks for just-in-time design smells prediction using fine-grained software metrics. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (Neurocomputing, 2021)

An empirical study on the co-occurrence between refactoring actions and Self-Admitted Technical Debt removal. - Martina Iammarino; Fiorella Zampetti; Lerina Aversano; Massimiliano Di Penta (J. Syst. Softw., 2021)

Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy. - Lerina Aversano; Mario Luca Bernardi; Vincenzo Calgano; Marta Cimitile; Concetta Esposito; Martina Iammarino; Marco Pisco; Sara Spaziani; Chiara Verdone (DeLTA, 2022)

Using Machine Learning for early prediction of Heart Disease. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano; Chiara Verdone (EAIS, 2022)

A Machine Learning approach for Early Detection of Parkinson's Disease Using acoustic traces. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano; Chiara Verdone (EAIS, 2022)

An Empirical Study to Predict Student Performance Using Information of the Virtual Learning Environment. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano; Chiara Verdone (HELMeTO, 2022)

Is There Any Correlation between Refactoring and Design Smell Occurrence? - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano (ICSOFT, 2022)

Early Detection of Parkinson's Disease using Spiral Test and Echo State Networks. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Chiara Verdone (IJCNN, 2022)

An enhanced UNet variant for Effective Lung Cancer Detection. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Chiara Verdone (IJCNN, 2022)

Technical Debt Forecasting from Source Code Using Temporal Convolutional Networks. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (PROFES, 2022)

Using deep temporal convolutional networks to just-in-time forecast technical debt principal. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (J. Syst. Softw., 2022)

Just-in-time software defect prediction using deep temporal convolutional networks. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (Neural Comput. Appl., 2022)

Machine Learning Applied to Speech Recordings for Parkinson's Disease Recognition. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Antonella Madau; Chiara Verdone (DeLTA, 2023)

An Explainable Approach for Early Parkinson Disease Detection Using Deep Learning. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Antonella Madau; Chiara Verdone (DeLTA, 2023)

An Empirical Study on the Relationship Between the Co-Occurrence of Design Smell and Refactoring Activities. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano (ENASE, 2023)

Early Parkinson's Disease Detection from EEG Traces Using Machine Learning Techniques. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano; Chiara Verdone (EUSFLAT/AGOP, 2023)

Understanding Compiler Effects on Clone Detection Process. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano (ICSOFT, 2023)

Early Diagnosis of Parkinson's Disease Exploting Motor and Non-Motor Symptoms: Results from the PPMI Cohort. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Antonella Madau; Chiara Verdone (KES, 2023)

Raman Spectroscopy of Cells for Cancer Classification Through Machine Learning. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Andrea Cusano; Martina Iammarino; Marco Pisco; Sara Spaziani; Chiara Verdone (MetroXRAINE, 2023)

Forecasting the Developer's Impact in Managing the Technical Debt. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (PROFES (2), 2023)

Forecasting technical debt evolution in software systems: an empirical study. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Debora Montano (Frontiers Comput. Sci., 2023)

Evo-GUNet3++: Using evolutionary algorithms to train UNet-based architectures for efficient 3D lung cancer detection. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Chiara Verdone (Appl. Soft Comput., 2023)

A data-aware explainable deep learning approach for next activity prediction. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Chiara Verdone (Eng. Appl. Artif. Intell., 2023)

Adopting Delta Maintainability Model for Just in Time Bug Prediction. - Lerina Aversano; Martina Iammarino; Antonella Madau; Debora Montano; Chiara Verdone (ICSOFT, 2024)

A Machine Learning Approach for the Detection of Thoracic Disease using Chest X-ray reports. - Lerina Aversano; Martina Iammarino; Antonella Madau; Debora Montano; Chiara Verdone (KES, 2024)

Raman Spectroscopy of Cancer Cells: An Explainable Classification Model. - Andrea Cusano; Martina Iammarino; Marco Pisco; Sara Spaziani; Chiara Verdone (MetroXRAINE, 2024)

A systematic review on artificial intelligence approaches for smart health devices. - Lerina Aversano; Martina Iammarino; Ilaria Mancino; Debora Montano (PeerJ Comput. Sci., 2024)

An Explainable Model for Waste Cost Prediction: A Study on Linked Open Data in Italy. - Lerina Aversano; Martina Iammarino; Antonella Madau; Debora Montano; Chiara Verdone (ICSOFT, 2025)

What Time Is It? Finding Which Temporal Features is More Useful for Next Activity Prediction. - Lerina Aversano; Martina Iammarino; Antonella Madau; Giuseppe Pirlo; Gianfranco Semeraro (IEEE Open J. Comput. Soc., 2025)

Process mining applications in healthcare: a systematic literature review. - Lerina Aversano; Martina Iammarino; Antonella Madau; Giuseppe Pirlo; Gianfranco Semeraro (PeerJ Comput. Sci., 2025)