Università della Svizzera italiana

Artificial intelligence in thyroid field : a comprehensive review

Bini, Fabiano ; Pica, Andrada ; Azzimonti, Laura ; Giusti, Alessandro ; Ruinelli, Lorenzo ; Marinozzi, Franco ; Trimboli, Pierpaolo

In: Cancers, 2021, vol. 13, no. 19, p. 18

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to...

Università della Svizzera italiana

A new constructive heuristic driven by machine learning for the traveling salesman problem

Mele, Umberto Junior ; Gambardella, Luca Maria ; Montemanni, Roberto

In: Algorithms, 2021, vol. 14, no. 9, p. 25

Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...

Università della Svizzera italiana

Testing machine learning based systems : a systematic mapping

Riccio, Vincenzo ; Jahangirova, Gunel ; Stocco, Andrea ; Humbatova, Nargiz ; Weiss, Michael ; Tonella, Paolo

In: Empirical Software Engineering, 2020, vol. 25, no. 6, p. 5193–5254

Context: A Machine Learning based System (MLS) is a software system including one or more components that learn how to perform a task from a given data set. The increasing adoption of MLSs in safety critical domains such as autonomous driving, healthcare, and finance has fostered much attention towards the quality assurance of such systems. Despite the advances in software testing, MLSs bring...

Università della Svizzera italiana

Gaussian mean field regularizes by limiting learned information

Kunze, Julius ; Kirsch, Louis ; Ritter, Hippolyt ; Barber, David

In: Entropy, 2019, vol. 21, no. 8, p. 758

Variational inference with a factorized Gaussian posterior estimate is a widely-used approach for learning parameters and hidden variables. Empirically, a regularizing effect can be observed that is poorly understood. In this work, we show how mean field inference improves generalization by limiting mutual information between learned parameters and the data through noise. We quantify a...

Università della Svizzera italiana

Leukocyte tracking database, a collection of immune cell tracks from intravital 2-photon microscopy videos

Pizzagalli, Diego Ulisse ; Farsakoglu, Yagmur ; Palomino-Segura, Miguel ; Palladino, Elisa ; Sintes, Jordi ; Marangoni, Francesco ; Mempel, Thorsten R. ; Koh, Wan Hon ; Murooka, Thomas T. ; Thelen, Flavian ; Stein, Jens V. ; Pozzi, Giuseppe ; Marcus Thelen ; Krause, Rolf ; Gonzalez, Santiago Fernandez

In: Scientific data, 2018, vol. 5, p. 180129

Recent advances in intravital video microscopy have allowed the visualization of leukocyte behavior in vivo, revealing unprecedented spatiotemporal dynamics of immune cell interaction. However, state-of-the-art software and methods for automatically measuring cell migration exhibit limitations in tracking the position of leukocytes over time. Challenges arise both from the complex migration...