Nicoletta Prentzas

According to our database, Nicoletta Prentzas authored at least 8 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Explainable AI applications in the Medical Domain: a systematic review.

Nicoletta Prentzas, Antonis C. Kakas, Constantinos S. Pattichis

CoRR, 2023

Explainable Machine Learning via Argumentation.

Nicoletta Prentzas, Constantinos S. Pattichis, Antonis C. Kakas

Proceedings of the Explainable Artificial Intelligence, 2023

Argumentation-based Explainable Machine Learning ArgEML: α-Version Technical Details.

Nicoletta Prentzas

Proceedings of the Joint Proceedings of the xAI-2023 Late-breaking Work, 2023

A Comparative Study of Explainable AI models in the Assessment of Multiple Sclerosis.

Andria Nicolaou, Nicoletta Prentzas, Christos P. Loizou, Marios Pantzaris, Antonis C. Kakas, Constantinos S. Pattichis

Proceedings of the Computer Analysis of Images and Patterns, 2023

2022

Argumentation-based Explainable Machine Learning (ArgEML): a Real-life Use Case on Gynecological Cancer.

Nicoletta Prentzas, Athena Gavrielidou, Marios Neofytou, Antonis C. Kakas

Proceedings of the 1st Workshop on Argumentation & Machine Learning co-located with 9th International Conference on Computational Models of Argument (COMMA 2022), 2022

2021

Model Agnostic Explainability Techniques in Ultrasound Image Analysis.

Nicoletta Prentzas, Marios Pitsiali, Efthyvoulos Kyriacou, Andrew Nicolaides, Antonis C. Kakas, Constantinos S. Pattichis

Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

2020

Extracting Explainable Assessments of Alzheimer's disease via Machine Learning on brain MRI imaging data.

Kleo G. Achilleos, Stephanos Leandrou, Nicoletta Prentzas, Panayiotis A. Kyriacou, Antonis C. Kakas, Constantinos S. Pattichis

Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

2019

Integrating Machine Learning with Symbolic Reasoning to Build an Explainable AI Model for Stroke Prediction.

Nicoletta Prentzas, Andrew Nicolaides, Efthyvoulos Kyriacou, Antonis C. Kakas, Constantinos S. Pattichis

Proceedings of the 19th IEEE International Conference on Bioinformatics and Bioengineering, 2019