Fernando C. Barros

Federal University of Pelotas (UFPel) - Postgraduate Program in Epidemiology

Rua Marechal Deodoro, 1160 - 3° Piso

Pelotas

Brazil

SCHOLARLY PAPERS

3

DOWNLOADS

360

SSRN CITATIONS

3

CROSSREF CITATIONS

0

Scholarly Papers (3)

1.

Remarkable Variability in SARS-CoV-2 Antibodies across Brazilian Regions: Report on Two Successive Nationwide Serological Household Surveys

Number of pages: 24 Posted: 13 Jul 2020
Federal University of Pelotas (UFPel), Federal University of Pelotas (UFPel), Federal University of Pelotas (UFPel) - Postgraduate Program in Epidemiology, Pan American Health Organization, Women and Reproductive Health, CLAP SMR PAHO/WHO Latin American Center of Perinatology, Federal University of Pelotas (UFPel), Federal University of Pelotas (UFPel), Pastorate of the Child, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Federal University of Pelotas (UFPel), Federal University of São Paulo (UNIFESP), Federal University of Pelotas (UFPel), Federal University of Pelotas (UFPel) - Postgraduate Program in Epidemiology, Federal University of Pelotas (UFPel) and Federal University of Pelotas (UFPel) - International Center for Equity in Health (ICEH)
Downloads 196 (290,884)
Citation 1

Abstract:

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COVID-19, SARS-CoV-2, seroprevalence surveys, Brazil, socioeconomic factors

2.

Early Detection of Bipolar Disorder Four Years Before Onset in a 22-Year Population-Based Birth Cohort Using Advanced Machine Learning Techniques

Number of pages: 28 Posted: 07 Apr 2020
Hospital de Porto Alegre - Molecular Psychiatry Laboratory, Hospital de Porto Alegre - Molecular Psychiatry Laboratory, University of Texas at Houston - Health Science Center at Houston (UTHealth), Federal University of Pelotas (UFPel) - Postgraduate Program in Epidemiology, Federal University of Pelotas (UFPel) - International Center for Equity in Health (ICEH), McMaster University, McMaster University, Universidade Federal do Rio Grande do Sul (UFRGS) - Bipolar Disorder Program and Hospital de Porto Alegre - Molecular Psychiatry Laboratory
Downloads 82 (564,798)

Abstract:

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bipolar disorder; machine learning; Prediction; illness progression

3.

Using Machine Learning to Achieve Accurate Estimates of Fetal Gestational Age and Personalized Predictions of Fetal Growth

Number of pages: 42 Posted: 28 Oct 2019
University of Wisconsin - Milwaukee - Department of Physics, University of Oxford, University of Wisconsin - Milwaukee - Department of Physics, University of Sharjah, University of Oxford, University of Oxford, Universite Paris Descartes, Federal University of Pelotas (UFPel) - International Center for Equity in Health (ICEH), Federal University of Pelotas (UFPel) - Postgraduate Program in Epidemiology, University of Oxford, Aga Khan University, Ministry of Health (Oman), University of Oxford - Department of Engineering Science, Global Alliance to Prevent Prematurity and Stillbirth, Ketkar Hospital, Peking University, Universita di Torino, Aga Khan University, Mahidol University, Mahidol University, University of the Witwatersrand, University of Toronto - Centre for Global Child Health, University of Oxford, University of Oxford, University of Wisconsin - Milwaukee - Department of Physics and Independent
Downloads 82 (564,798)

Abstract:

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