Deep learning can differentiate IDH-mutant from IDH-wild type GBM

no code implementations • 24 Feb 2021 • Luca Pasquini, Antonio Napolitano, Emanuela Tagliente, Francesco Dellepiane, Martina Lucignani, Antonello Vidiri, Giulio Ranazzi, Antonella Stoppacciaro, Giulia Moltoni, Matteo Nicolai, Andrea Romano, Alberto Di Napoli, Alessandro Bozzao

Conclusion: We built a GBM-tailored deep-learning model for IDH mutation prediction, achieving accuracy of 83% with rCBV maps.

Vocal Bursts Type Prediction

Comparison of Machine Learning Classifiers to Predict Patient Survival and Genetics of GBM: Towards a Standardized Model for Clinical Implementation

no code implementations • 10 Feb 2021 • Luca Pasquini, Antonio Napolitano, Martina Lucignani, Emanuela Tagliente, Francesco Dellepiane, Maria Camilla Rossi-Espagnet, Matteo Ritrovato, Antonello Vidiri, Veronica Villani, Giulio Ranazzi, Antonella Stoppacciaro, Andrea Romano, Alberto Di Napoli, Alessandro Bozzao

We aimed to compare nine machine learning classifiers, with different optimization parameters, to predict overall survival (OS), isocitrate dehydrogenase (IDH) mutation, O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, epidermal growth factor receptor (EGFR) VII amplification and Ki-67 expression in GBM patients, based on radiomic features from conventional and advanced MR. 156 adult patients with pathologic diagnosis of GBM were included.

Cosmic Ray Extremely Distributed Observatory

no code implementations • 16 Oct 2020 • Piotr Homola, Dmitriy Beznosko, Gopal Bhatta, Lukasz Bibrzycki, Michalina Borczynska, Lukasz Bratek, Nikolai Budnev, Dariusz Burakowski, David E. Alvarez-Castillo, Kevin Almeida Cheminant, Aleksander Cwikla, Punsiri Dam-o, Niraj Dhital, Alan R. Duffy, Piotr Glownia, Krzysztof Gorzkiewicz, Dariusz Gora, Alok C. Gupta, Zuzana Hlavkova, Martin Homola, Joanna Jalocha, Robert Kaminski, Michal Karbowiak, Marcin Kasztelan, Renata Kierepko, Marek Knap, P eter Kov acs, Szymon Kuli nski, Bartosz L ozowski, Marek Magrys, Mikhail V. Medvedev, Justyna Mkedrala, Jerzy W. Mietelski, Justyna Miszczyk, Alona Mozgova, Antonio Napolitano, Vahab Nazari, Y. Jack Ng, Michal Niedzwiecki, Cristina Oancea, Boguslaw Ogan, Gabriela Opila, Krzysztof Oziomek, Maciej Pawlik, Marcin Piekarczyk, Bozena Poncyliusz, Jerzy Pryga, Matias Rosas, Krzysztof Rzecki, Jilberto Zamora-Saa, Katarzyna Smelcerz, Karel Smolek, Weronika Stanek, Jaroslaw Stasielak, Slawomir Stuglik, Jolanta Sulma, Oleksandr Sushchov, Manana Svanidze, Kyle Tam, Arman Tursunov, Jose M. Vaquero, Tadeusz Wibig, Krzysztof W. Wozniak

The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary interaction vertex or the same parent particle.

High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics