Discriminating Healthy and IUGR fetuses through Machine Learning models. - Beniamino Daniele; Giulio Steyde; Edoardo Spairani; Giovanni Magenes; Maria G. Signorini (BHI, 2022)

Influence of Gestational Diabetes on Fetal Heart Rate in Antepartum Cardiotocographic Recordings. - Giulio Steyde; Beniamino Daniele; Edoardo Spairani; Giovanni Magenes; Maria Gabriella Signorini (CinC, 2022)

Fetal states identification in cardiotocographic tracings through discrete emissions multivariate hidden Markov models. - Edoardo Spairani; Giulio Steyde; Salvatore Tagliaferri; Maria G. Signorini; Giovanni Magenes (Comput. Methods Programs Biomed., 2023)

Subject-Specific Feature Identification of Arousal and Valence Based on EEG. - Edoardo Maria Polo; Andrea Farabbi; Maja Milekic; Giulio Steyde; Maria Gabriella Signorini; Patrícia Figueiredo; Luca T. Mainardi; Riccardo Barbieri (MeMeA, 2024)

Asemi-Supervised Deep Learning Approach to Automate the Identification of Fetal Behavioral States in Fetal Heart Rate Tracings. - Edoardo Spairani; Giulio Steyde; Luca Subitoni; Giovanni Magenes; Maria G. Signorini (MeMeA, 2024)

Fetal heart rate spectral analysis in raw signals and PRSA-derived curve: normal and pathological fetuses discrimination. - Giulio Steyde; Edoardo Spairani; Giovanni Magenes; Maria G. Signorini (Medical Biol. Eng. Comput., 2024)

Semi-simulated Data for Improving Fetal QRS Detection Using Deep Neural Networks. - Giulio Steyde; Alessandra Galli; Andrea Cardinali; Edoardo Spairani; Giovanni Magenes; Maria G. Signorini (AIME (2), 2025)

Prediction of IUGR condition at birth by means of CTG recordings and a ResNet model. - Edoardo Spairani; Giulio Steyde; Federica Spuri Forotti; Giovanni Magenes; Maria G. Signorini (Comput. Biol. Medicine, 2025)