AI-Enabled Solutions, Explainability and Ethical Concerns for Predicting Sepsis in ICUs: A Systematic Review. - Christina-Athanasia I. Alexandropoulou; Ilias E. Panagiotopoulos; Styliani Kleanthous; George Dimitrakopoulos 001; Ioannis Constantinou; Elena Politi; Dimitrios Ntalaperas; Xanthi S. Papageorgiou; Charithea Stylianides; Nikos Ioannides; Lakis Palazis; Constantinos S. Pattichis; et al. (e-Science, 2023)

A Study of Data-Driven Methods for Adaptive Forecasting of COVID-19 Cases. - Charithea Stylianides; Kleanthis Malialis; Panayiotis Kolios (ICANN (1), 2023)

Time-varying compartmental models with neural networks for pandemic infection forecasting. - Marianna Karapitta; Andreas Kasis; Charithea Stylianides; Kleanthis Malialis; Panayiotis Kolios (EMBC, 2024)

Emergency Department Length of Stay Classification Based on Ensemble Methods and Rule Extraction. - Waqar Aziz; Andria Nicalaou; Charithea Stylianides; Andreas Panayides; Antonis C. Kakas; Efthyvoulos C. Kyriacou; Constantinos S. Pattichis (MIE, 2024)

Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction. - Waqar A. Sulaiman; Charithea Stylianides; Andria Nikolaou; Zinonas C. Antoniou; Ioannis Constantinou; Lakis Palazis; Anna Vavlitou; Theodoros Kyprianou; Efthyvoulos Kyriacou; Antonis C. Kakas; Marios S. Pattichis; Andreas S. Panayides; et al. (Frontiers Digit. Health, 2024)

Fairness-Aware Graph Neural Networks for ICU Length of Stay Prediction in IoT-Enabled Environments. - Angelos-Christos Maroudis; Konstantina Karathanasopoulou; Charithea Stylianides; George Dimitrakopoulos 001; Andreas S. Panayides (IEEE Access, 2025)

AI Advances in ICU with an Emphasis on Sepsis Prediction: An Overview. - Charithea Stylianides; Andria Nicolaou; Waqar A. Sulaiman; Christina-Athanasia I. Alexandropoulou; Ilias E. Panagiotopoulos; Konstantina Karathanasopoulou; George Dimitrakopoulos 001; Styliani Kleanthous; Eleni Politi; Dimitris Ntalaperas; Xanthi S. Papageorgiou; Fransisco Garcia; et al. (Mach. Learn. Knowl. Extr., 2025)