Sara Cammarota

Dottorandi

sara.cammarota@hotmail.it

+39 06 72596008

Biografia

Sara è una studentessa del Programma Nazionale di Dottorato in Intelligenza Artificiale presso la Sezione di Fisica Medica di Tor Vergata.

Ha conseguito la laurea triennale in Fisica presso l’Università La Sapienza di Roma, dove ha sviluppato una tesi sull’uso dei fotomoltiplicatori al silicio nella tomografia a emissione di positroni. Successivamente ha conseguito un master in Data Science, concentrandosi su Topological Deep Learning e Semantic Communications.

I suoi interessi di ricerca si concentrano in particolare sulle reti neurali a grafo e sull’apprendimento profondo topologico, in particolare su come le architetture neurali informate dalla topologia possano elaborare dati biologici complessi e strutturati e fornire informazioni utili.

Last 5 articles (Scopus)

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Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging; Computer Methods and Programs in Biomedicine; November 2024; DOI: 10.1016/j.cmpb.2024.108375
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Cortical structure and subcortical volumes in conduct disorder: a coordinated analysis of 15 international cohorts from the ENIGMA-Antisocial Behavior Working Group; The Lancet Psychiatry; August 2024; DOI: 10.1016/S2215-0366(24)00187-1
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Retrieving and reconstructing conceptually similar images from fMRI with latent diffusion models and a neuro-inspired brain decoding model; Journal of Neural Engineering; 1 August 2024; DOI: 10.1088/1741-2552/ad593c
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Decoding visual brain representations from electroencephalography through knowledge distillation and latent diffusion models; Computers in Biology and Medicine; August 2024; DOI: 10.1016/j.compbiomed.2024.108701
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Unraveling sex differences in Parkinson's disease through explainable machine learning; Journal of the Neurological Sciences; 15 July 2024; DOI: 10.1016/j.jns.2024.123091
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Last 5 articles (PubMed)

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