Carolina Momoli, Beatrice Costa, Lorenzo Lenti, Matilde Tubertini, Marco Daniele Parenti, Elisa Martella, Greta Varchi, Claudia Ferroni
Beatrice Costa was not included as a first co-author in the original publication [...]
Catharina Silvia Lisson, Christoph Gerhard Lisson, Marc Fabian Mezger, Daniel Wolf, Stefan Andreas Schmidt, Wolfgang M. Thaiss, et al.
Mantle cell lymphoma (MCL) is a rare lymphoid malignancy with a poor prognosis characterised by frequent relapse and short durations of treatment response. Most patients present with aggressive disease, but there exist indolent subtypes without the need for immediate intervention…
Carolina Momoli, Beatrice Costa, Lorenzo Lenti, Matilde Tubertini, Marco Parenti, Elisa Martella, et al.
The development of anticancer therapies has increasingly relied on advanced 3D in vitro models, which more accurately mimic the tumor microenvironment compared to traditional 2D cultures. This review describes the evolution of these 3D models, highlighting significant advancement…
Background/Objectives: This study aims to evaluate the performance of various classification algorithms and resampling methods across multiple diagnostic and prognostic cancer datasets, addressing the challenges of class imbalance. Methods: A total of five datasets were analyzed,…
Wojciech Górski, Marcin Kubiak, Amir Nour Mohammadi, Maksymilian Podleśny, Gian Luca Baiocchi, Manuele Gaioni, et al.
Introduction: By leveraging dedicated datasets and predictive modeling, machine-learning (ML) algorithms can estimate the probability of both short- and long-term outcomes after surgery. The aim of this study was to evaluate the ability of ML-based models to predict postoperative…
Rossella Reddavid, Ugo Elmore, Jacopo Moro, Paola De Nardi, Alberto Biondi, Roberto Persiani, et al.
Background: Almost 30% of patients with rectal cancer (RC) who submit to comprehensive treatment experience relapse. Surveillance plays a leading role in early detection. The landmark approach provides a more flexible and dynamic framework for survival prediction. Objective: This…
Samet Yagci, Evrim Erdemoglu, Mehmet Erdogan, Mustafa Avci, Ahmet Tunc, Ismail Ozkoc, et al.
Purpose: Accurate preoperative risk stratification in endometrial cancer (EC) is essential for guiding surgical and therapeutic decisions. This study aimed to evaluate the discriminative performance of [18F]-FDG PET/CT-derived radiomic features combined with machine learning mode…