A5068075782- Neural dynamics and brain function
- Multiple Sclerosis Research Studies
- Visual perception and processing mechanisms
- Neural Networks and Applications
- Image and Signal Denoising Methods
- Rheumatoid Arthritis Research and Therapies
- Cell Image Analysis Techniques
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Autism Spectrum Disorder Research
- Statistical Methods in Clinical Trials
- Action Observation and Synchronization
- Image Retrieval and Classification Techniques
- CCD and CMOS Imaging Sensors
- Advanced X-ray and CT Imaging
- COVID-19 and Mental Health
- BRCA gene mutations in cancer
- Bioinformatics and Genomic Networks
- Face and Expression Recognition
- Parathyroid Disorders and Treatments
- Control and Stability of Dynamical Systems
- Mental Health and Psychiatry
- Neural and Behavioral Psychology Studies
- Medical Image Segmentation Techniques
- Brain Tumor Detection and Classification
- Peripheral Neuropathies and Disorders
University of Genoa
2024-2025
Department of Medical Sciences
2024-2025
Italian Institute of Technology
2021-2024
University of Bologna
2019-2020
Background: Randomized clinical trials (RCTs) in progressive multiple sclerosis (MS) often revealed non-significant treatment effects on disability progression. Objectives: To investigate whether the failure to detect a significant benefit from may be motivated by delay effect, possibly related baseline characteristics. Methods: We re-analyzed data two RCTs testing interferon-beta and glatiramer-acetate versus placebo MS with no effect EDSS first designed time-dependent Cox model up time = t...
Abstract Background/Introduction The diagnosis of transthyretin-related cardiac amyloidosis (ATTR-CA), while often suggested by red flags observed in echocardiography, still requires a lengthy and multi-step process. Recent evidence indicates the feasibility using radiomics on echocardiographic images (i.e., echomics) for early characterization myocardial texture anomalies ATTR-CA. Aims This study aims to develop radiomic-based model (ATTR-CA) characterizing tissue through echocardiography...
Significance A major challenge in studying intention reading is high motor variability. Analyses conducted across trials provide insights into what happens on average; however, they may obscure how individual observers read information movements. We combined motion tracking, psychophysics, and computational analyses to examine autism spectrum disorders (ASDs) with single-trial resolution. Results revealed that a sizeable fraction of ASD can identify intention-informative variations (but not...
Abstract Aberrant motor-sensory predictive functions have been linked to symptoms of psychosis, particularly reduced attenuation self-generated sensations and misattribution actions. Building on the parallels between prediction self- other-generated actions, this study aims investigate whether individuals with psychosis also demonstrate abnormal perceptions predictions others’ Patients matched controls completed a two-alternative object size discrimination task. In each trial, they observed...
Objective The introduction of disease‐modifying therapies for multiple sclerosis (MS) has led to a deceleration disease course over the years. Although decreased relapse rate constitutes factor, role relapse‐associated worsening (RAW) and progression independent activity (PIRA) in MS is still unclear. Methods We retrospectively examined long‐term Expanded Disability Status Scale (EDSS) patients referred Center Montichiari (Italy) diagnosed with relapsing–remitting from 1980 2022. To isolate...
Background: The lack of standardized disability progression evaluation in multiple sclerosis (MS) hinders reproducibility clinical study results, due to heterogeneous and poorly reported criteria. Objective: To demonstrate the impact using different parameters when evaluating MS progression, introduce an automated tool for reproducible outcome computation. Methods: Re-analyzing BRAVO trial data (NCT00605215), we examined fluctuations computed treatment effect on confirmed (CDP) independent...
The state of the art in many computer vision tasks is represented by Convolutional Neural Networks (CNNs). Although their hierarchical organization and local feature extraction are inspired structure primate visual systems, lack lateral connections such architectures critically distinguishes analysis from biological object processing. idea enriching CNNs with recurrent convolutional type has been put into practice recent years, form learned kernels no geometrical constraints. In present...
The purpose of this work is to construct a model for the functional architecture primary visual cortex (V1), based on structure metric measure space induced by underlying organization receptive profiles (RPs) cells. In order account horizontal connectivity V1 in such context, diffusion process compatible with geometry defined following classical approach K.-T. Sturm [Ann. Probab., 26 (1998), pp. 1--55]. construction our distance function neither requires any group parameterization family RPs...
In this paper we study the spontaneous development of symmetries in early layers a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built such way to mimic some properties stages biological visual systems. particular, it contains pre-filtering step ℓ0 defined analogy with Lateral Geniculate Nucleus (LGN). Moreover, first convolutional layer equipped lateral connections as propagation driven by learned connectivity kernel, horizontal primary cortex...
Abstract Background The lack of standardized disability progression evaluation in multiple sclerosis (MS) hinders reproducibility clinical study results, due to heterogeneous and poorly reported criteria. Objectives To demonstrate the impact using different parameters when evaluating MS progression, introduce an automated tool for reproducible outcome computation. Methods Re-analyzing BRAVO trial data ( NCT00605215 ), we examined fluctuations computed treatment effect on confirmed (CDP)...
<title>Abstract</title> Background Collecting high quality, patient level data demands significant efforts and resources. A potential solution, well-suited for exploratory hypothesis testing, gathering evidence, assessing the heterogeneity generalizability of estimates, is usage synthetic data. Synthetic are newly generated from real, original They share a fundamental set statistical properties, which sufficient to replicate analysis findings. Aim this work explore feasibility obtaining...
Abstract Background Granular sparkling is a well-known echocardiographic feature found in patients with transthyretin-related cardiac amyloidosis (ATTR-CA). However, there no objective technique for quantifying this feature, which therefore remains qualitative, elusive and ultimately unreliable imaging characteristic. Recent evidence suggests that radiomics and, particular, ultrasonomics could play an important role the non-invasive tissue characterization of cardiomyopathies through study...
This decision analytical applies restricted mean survival time as a measure of treatment effect in 2 randomized clinical trials assessing disease-modifying treatments vs placebo patients with progressive multiple sclerosis.
The purpose of this work is to construct a model for the functional architecture primary visual cortex (V1), based on structure metric measure space induced by underlying organization receptive profiles (RPs) cells. In order account horizontal connectivity V1 in such context, diffusion process compatible with geometry defined following classical approach K.-T. Sturm. construction our distance function does neither require any group parameterization family RPs, nor involve differential...