Manuele Bicego

University of Verona — Italy

Computer Science · Physical Sciences

27h-index2.7kcitations144works0.42yr avg
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Research Topics

Face and Expression Recognition(31), Anomaly Detection Techniques and Applications(22), Image Retrieval and Classification Techniques(20), Face recognition and analysis(19), Gene expression and cancer classification(18)

Publications144 total

FRI-167 AI-AD score: a novel machine learning-based model for predicting acute liver decompensation progression – a prospective observational study
Journal of Hepatology·2025
AI-AD score: a novel Machine Learning-based model for predicting Acute Liver Decompensation progression – a prospective observational study
Digestive and Liver Disease·2025
Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data
Lecture notes in computer science·2025Open Access
An Interesting Property of Random Forest Distances with Respect to the Curse of Dimensionality
Lecture notes in computer science·2025
An Empirical Characterization of the Stability of Isolation Forest Results
Lecture notes in computer science·2025
An Extension of Random Forest-Clustering Schemes Which Works with Partition-Level Constraints
Lecture notes in computer science·2024
Computing Random Forest-distances in the presence of missing data
ACM Transactions on Knowledge Discovery from Data·2024· 3 citedOpen Access
Improving the accuracy of multiple sclerosis classification via robust feature selection based on quantitative tractography
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition·2023
Also for k-means: more data does not imply better performance
Machine Learning·2023· 3 citedOpen Access
A Novel Kernel Extension for the Nearest Feature Line Classifier
2023
Null/No Information Rate (NIR): a statistical test to assess if a classification accuracy is significant for a given problem
arXiv (Cornell University)·2023· 10 citedOpen Access
Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
Internal and Emergency Medicine·2023· 3 citedOpen Access
Detecting outliers from pairwise proximities: Proximity isolation forests
Pattern Recognition·2023· 24 citedOpen Access
On the Good Behaviour of Extremely Randomized Trees in Random Forest-Distance Computation
Lecture notes in computer science·2023· 5 cited
Active Class Selection for Dataset Acquisition in Sign Language Recognition
Lecture notes in computer science·2023· 2 cited
Advanced KNN Approaches for Explainable Seismic-Volcanic Signal Classification
Mathematical Geosciences·2022· 15 cited
DisRFC: a dissimilarity-based Random Forest Clustering approach
Pattern Recognition·2022· 8 cited
Metabolic dysfunction-associated fatty liver disease and liver fibrosis score in patients with COVID-19 as predictors of adverse clinical outcomes: an artificial intelligent application through machine learning
Digestive and Liver Disease·2022Open Access
Using Random Forest Distances for Outlier Detection
Lecture notes in computer science·2022· 1 cited
Machine learning approaches for the automated classification of intraoperative motor evoked potentials. A pilot study
Brain and Spine·2022Open Access
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Frequent Co-authors

Vittorio Murino(18), Pietro Lovato(9), Marco Cristani(7), Mário A. T. Figueiredo(6), Alessandro Farinelli(6), Enrico Grosso(5), Mássimo Tistarelli(5), Alessandro Perina(5), Mauricio Orozco‐Alzate(4), Antonella Mensi(3), Jason Blum(3), John Makario Londoño(3), Alberto Castellini(3), Andrea Lagorio(2), Umberto Castellani(2), Sisto Baldo(2), Massimo Delledonne(2), Marco Loog(2), David M. J. Tax(2), Robert P. W. Duin(2)