Systematic review of existing guidelines for NAFLD assessment

F Monelli, F Venturelli, L Bonilauri, E Manicardi… - Hepatoma …, 2021 - iris.unimore.it
Aim: In this systematic review, guidelines on non-alcoholic fatty liver disease (NAFLD) were
evaluated, aiming at a guideline synthesis focusing on diagnosis and staging. Methods: A …

[HTML][HTML] Follow-up CT patterns of residual lung abnormalities in severe COVID-19 pneumonia survivors: a multicenter retrospective study

G Besutti, F Monelli, S Schirò, F Milone, M Ottone… - Tomography, 2022 - mdpi.com
Prior studies variably reported residual chest CT abnormalities after COVID-19. This study
evaluates the CT patterns of residual abnormalities in severe COVID-19 pneumonia …

[HTML][HTML] Abdominal visceral infarction in 3 patients with COVID-19

G Besutti, R Bonacini, V Iotti, G Marini… - Emerging Infectious …, 2020 - ncbi.nlm.nih.gov
A high incidence of thrombotic events has been reported in patients with coronavirus
disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 …

[HTML][HTML] Mortality prediction of COVID-19 patients using radiomic and neural network features extracted from a wide chest X-ray sample size: A robust approach for …

M Iori, C Di Castelnuovo, L Verzellesi, G Meglioli… - Applied Sciences, 2022 - mdpi.com
Aim: The aim of this study was to develop robust prognostic models for mortality prediction of
COVID-19 patients, applicable to different sets of real scenarios, using radiomic and neural …

[HTML][HTML] The effect of diffuse liver diseases on the occurrence of liver metastases in Cancer patients: A Systematic Review and Meta-Analysis

F Monelli, G Besutti, O Djuric, L Bonvicini, R Farì… - Cancers, 2021 - mdpi.com
Simple Summary Diffuse liver diseases have a high incidence among the general
population and even higher in patients with a solid cancer. Since many patients with a solid …

[HTML][HTML] Machine and deep learning algorithms for COVID-19 mortality prediction using clinical and radiomic features

L Verzellesi, A Botti, M Bertolini, V Trojani, G Carlini… - Electronics, 2023 - mdpi.com
Aim: Machine learning (ML) and deep learning (DL) predictive models have been employed
widely in clinical settings. Their potential support and aid to the clinician of providing an …

[HTML][HTML] Inflammatory burden and persistent CT lung abnormalities in COVID-19 patients

G Besutti, P Giorgi Rossi, M Ottone, L Spaggiari… - Scientific reports, 2022 - nature.com
Inflammatory burden is associated with COVID-19 severity and outcomes. Residual
computed tomography (CT) lung abnormalities have been reported after COVID-19. The aim …

Vessel inflammation and morphological changes in patients with large vessel vasculitis: a retrospective study

G Besutti, F Muratore, P Mancuso, M Ferrari, E Galli… - RMD open, 2022 - rmdopen.bmj.com
Objective The aim was to identify any association between imaging signs of vessel wall
inflammation (positron emission tomography–CT (PET-CT) score and CT/MR wall …

A practical artificial intelligence system to diagnose COVID-19 using computed tomography: a multinational external validation study

AA Ardakani, RM Kwee… - Pattern Recognition …, 2021 - Elsevier
Computed tomography has gained an important role in the early diagnosis of COVID-19
pneumonia. However, the ever-increasing number of patients has overwhelmed radiology …

[HTML][HTML] Imaging-based indices combining disease severity and time from disease onset to predict COVID-19 mortality: a cohort study

G Besutti, O Djuric, M Ottone, F Monelli, P Lazzari… - PLoS …, 2022 - journals.plos.org
Background COVID-19 prognostic factors include age, sex, comorbidities, laboratory and
imaging findings, and time from symptom onset to seeking care. Purpose The study aim was …