Výsledky vyhledávání - "Marina N. Silveira"

Akademický článek

ARTIFICIAL INTELLIGENCE TO EVALUATE METABOLIC TUMOR BURDEN IN PRIMARY STAGING OF RECTAL CANCER WITH 18F-FDG PET/CT

Autor: Victor Cabral Costa Ribeiro Heringer, Maria Carolina S. Mendes, Barbara Juarez Amorim, Allan Oliveira Santos, Marina N. Silveira, Cleide Silva, Juliano S. Fonseca, Mariana C.L. Lima, Lorena P. Cunha, Carlos Augusto R. Martinez, Claudio Coy, Jose Barreto C. Carvalheira, Elba Cristina Sá de Camargo Etchebehere

Publikováno v: Hematology, Transfusion and Cell Therapy, Vol 46, Iss , Pp S3-S4 (2024)

Introduction/Justification: The use of artificial intelligence using convolutional neural networks in clinical practice is recent. Thus, a growing need exists to validate software performance in different tasks in different diseases. Objectives: To e

Externí odkaz: https://doaj.org/article/f18eb707310049a9a660e90f58fbc945

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Akademický článek

Low skeletal muscle radiodensity and neutrophil-to-lymphocyte ratio as predictors of poor outcome in patients with COVID-19

Autor: Daniela M. H. Padilha, Maria C. S. Mendes, Fabiana Lascala, Marina N. Silveira, Lara Pozzuto, Larissa A. O. Santos, Lívia D. Guerra, Rafaella C. L. Moreira, Sandra R. Branbilla, Ademar D. C. Junior, Mateus B. O. Duarte, Maria L. Moretti, José B. C. Carvalheira

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)

Abstract Inflammatory states and body composition changes are associated with a poor prognosis in many diseases, but their role in coronavirus disease 2019 (COVID-19) is not fully understood. To assess the impact of low skeletal muscle radiodensity (

Externí odkaz: https://doaj.org/article/358edef15f8d45f395fc1754fb607b62

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Akademický článek

Construction of a nomogram for predicting COVID-19 in-hospital mortality: A machine learning analysis

Autor: Daniela M.H. Padilha, Gabriel R. Garcia, Gianni S.S. Liveraro, Maria C.S. Mendes, Maria E.S. Takahashi, Fabiana Lascala, Marina N. Silveira, Lara Pozzuto, Larissa A.O. Carrilho, Lívia D. Guerra, Rafaella C.L. Moreira, Sandra R. Branbilla, Sérgio S.J. Dertkigil, Jun Takahashi, José B.C. Carvalheira

Publikováno v: Informatics in Medicine Unlocked, Vol 36, Iss , Pp 101138- (2023)

Background and objectives: We aim to verify the use of ML algorithms to predict patient outcome using a relatively small dataset and to create a nomogram to assess in-hospital mortality of patients with COVID-19. Methods: A database of 200 COVID-19 p

Externí odkaz: https://doaj.org/article/485d9543d5b244dc9320e56843873242

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Low skeletal muscle radiodensity and neutrophil-to-lymphocyte ratio as predictors of poor outcome in patients with COVID-19

Publikováno v: Scientific reports. 12(1)

Inflammatory states and body composition changes are associated with a poor prognosis in many diseases, but their role in coronavirus disease 2019 (COVID-19) is not fully understood. To assess the impact of low skeletal muscle radiodensity (SMD), hig

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2eec14a12d27d1a2b486938586f90115
https://pubmed.ncbi.nlm.nih.gov/36127500

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