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)

Anomaly Detection of Medical IoT Traffic Using Machine Learning. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Debora Montano; Riccardo Pecori; Luca Veltri (DATA, 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)

Machine and Deep Learning Techniques to Classify Arousal Judgments in Dynamic Virtual Experience of Architecture. - Riccardo Pecori; Paolo Presti; Pietro Avanzini; Lerina Aversano; Fausto Caruana; Marta Cimitile; Debora Montano; Davide Ruzzon; Mario Luca Bernardi; Giovanni Vecchiato (ICMLA, 2023)

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

Early Diagnosis of Cardiac Diseases using ECG Images and CNN-2D. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Debora Montano; Riccardo Pecori (KES, 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)

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)

An Explainable Approach for Early Diagnosis of Parkinson's Disease Exploring Motor Symptoms. - Lerina Aversano; Antonella Madau; Debora Montano (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)

Characterization of Heart Diseases per Single Lead Using ECG Images and CNN-2D. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Debora Montano; Riccardo Pecori (Sensors, 2024)

Explainable Anomaly Detection of Synthetic Medical IoT Traffic Using Machine Learning. - Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Debora Montano; Riccardo Pecori; Luca Veltri (SN 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)