Zobrazeno 1 - 10 of 17 pro vyhledávání: '"Noemi Gozzi"'
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Akademický článek
Towards enhanced functionality of vagus neuroprostheses through in silico optimized stimulation
Autor: Federico Ciotti, Robert John, Natalija Katic Secerovic, Noemi Gozzi, Andrea Cimolato, Naveen Jayaprakash, Weiguo Song, Viktor Toth, Theodoros Zanos, Stavros Zanos, Stanisa Raspopovic
Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract Bioelectronic therapies modulating the vagus nerve are promising for cardiovascular, inflammatory, and mental disorders. Clinical applications are however limited by side-effects such as breathing obstruction and headache caused by non-speci
Externí odkaz: https://doaj.org/article/f961fa4d668f430fa89aa693cfe5e62c
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2
Akademický článek
Automated calibration of somatosensory stimulation using reinforcement learning
Autor: Luigi Borda, Noemi Gozzi, Greta Preatoni, Giacomo Valle, Stanisa Raspopovic
Publikováno v: Journal of NeuroEngineering and Rehabilitation, Vol 20, Iss 1, Pp 1-16 (2023)
Abstract Background The identification of the electrical stimulation parameters for neuromodulation is a subject-specific and time-consuming procedure that presently mostly relies on the expertise of the user (e.g., clinician, experimenter, bioengine
Externí odkaz: https://doaj.org/article/b1cc9e933ca648cbb862b36f761dfd59
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3
Akademický článek
Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs
Autor: Noemi Gozzi, Edoardo Giacomello, Martina Sollini, Margarita Kirienko, Angela Ammirabile, Pierluca Lanzi, Daniele Loiacono, Arturo Chiti
Publikováno v: Diagnostics, Vol 12, Iss 9, p 2084 (2022)
To identify the best transfer learning approach for the identification of the most frequent abnormalities on chest radiographs (CXRs), we used embeddings extracted from pretrained convolutional neural networks (CNNs). An explainable AI (XAI) model wa
Externí odkaz: https://doaj.org/article/ab1abe57babe468b9ac1fde6ff2a73dc
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4
Preoperative [11C]methionine PET to personalize treatment decisions in patients with lower-grade gliomas
Autor: Gaia Ninatti, Martina Sollini, Beatrice Bono, Noemi Gozzi, Daniil Fedorov, Lidija Antunovic, Fabrizia Gelardi, Pierina Navarria, Letterio S Politi, Federico Pessina, Arturo Chiti
Publikováno v: Neuro-Oncology. 24:1546-1556
Background PET with radiolabeled amino acids is used in the preoperative evaluation of patients with glial neoplasms. This study aimed to assess the role of [11C]methionine (MET) PET in assessing molecular features, tumor extent, and prognosis in new
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0de0d1a8a7e158be73cf8902c857d1f7
https://doi.org/10.1093/neuonc/noac040
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5
The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the 'Real World'?
Autor: Martina Sollini, Margarita Kirienko, Noemi Gozzi, Alessandro Bruno, Chiara Torrisi, Luca Balzarini, Emanuele Voulaz, Marco Alloisio, Arturo Chiti
Publikováno v: Cancers, 15 (2)
Cancers; Volume 15; Issue 2; Pages: 357
(1) Background: Once lung lesions are identified on CT scans, they must be characterized by assessing the risk of malignancy. Despite the promising performance of computer-aided systems, some limitations related to the study design and technical issu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cceded91f8d6e8cb2128a11efaddcd1
https://hdl.handle.net/20.500.11850/596869
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6
Multiparametric non-linear TENS modulation to integrate intuitive sensory feedback
Autor: Vittoria Bucciarelli, Noemi Gozzi, Natalija Katic, Giovanna Aiello, Margherita Razzoli, Giacomo Valle, Stanisa Raspopovic
Publikováno v: Journal of Neural Engineering, 20 (3)
Objective. Transcutaneous electrical nerve stimulation (TENS) has been recently introduced in neurorehabilitation and neuroprosthetics as a promising, non-invasive sensory feedback restoration alternative to implantable neurostimulation. Yet, the ado
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a772a117b53e9b059128ace7253cc9e1
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8
State-of-the-art of FAPI-PET imaging: a systematic review and meta-analysis
Autor: Noemi Gozzi, Martina Sollini, Fabrizia Gelardi, Arturo Chiti, Margarita Kirienko, Francesco Fiz
Publikováno v: European Journal of Nuclear Medicine and Molecular Imaging. 48:4396-4414
Introduction Fibroblast Activation Protein-α (FAPα) is overexpressed on cancer-associated fibroblasts in approximately 90% of epithelial neoplasms, representing an appealing target for therapeutic and molecular imaging applications. [68Ga]Ga-labell
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2890a6f24a301f9393187922f0be11f5
https://doi.org/10.1007/s00259-021-05475-0
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9
Image embeddings extracted from CNNs outperform other transfer learning approaches in chest radiographs’ classification
Autor: Noemi Gozzi, Edoardo Giacomello, Martina Sollini, Margarita Kirienko, Angela Ammirabile, Pierluca Lanzi, Daniele Loiacono, Arturo Chiti
Purpose To identify the best transfer learning approach in the identification of the most frequent abnormalities on chest radiograph (CXR) using embeddings extracted from pre-trained convolutional neural networks (CNNs). Explainable AI (XAI) model wa
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::caf82e46ceb9d5d5a46f37bf29f042b1
https://doi.org/10.21203/rs.3.rs-1361817/v1
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10
Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer
Autor: Isabella Castiglioni, Giulia Soldà, Martina Sollini, Marinella Corbetta, Arturo Chiti, Rosanna Asselta, Matteo Interlenghi, Emanuele Voulaz, Noemi Gozzi, Stefano Duga, Margarita Kirienko, Francesca Gallivanone
Publikováno v: European Journal of Nuclear Medicine and Molecular Imaging
European journal of nuclear medicine and molecular imaging (Internet) 48 (2021): 3643–3655. doi:10.1007/s00259-021-05371-7
info:cnr-pdr/source/autori:Kirienko M.; Sollini M.; Corbetta M.; Voulaz E.; Gozzi N.; Interlenghi M.; Gallivanone F.; Castiglioni I.; Asselta R.; Duga S.; Soldà G.; Chiti A./titolo:Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer/doi:10.1007%2Fs00259-021-05371-7/rivista:European journal of nuclear medicine and molecular imaging (Internet)/anno:2021/pagina_da:3643/pagina_a:3655/intervallo_pagine:3643–3655/volume:48
Objective The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC). Methods In this retrospective single-centre observational study, we selected 1
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc4f447b7668307f5e7ac746c9dca4b7
http://europepmc.org/articles/PMC8440255
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