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Diedre Santos do Carmo

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Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação (FEEC)  (Institutional affiliation for the last research proposal)
Birthplace: Brazil

Diedre works with AI, computer vision and image processing since undergraduate research projects in 2013 to current PhD studies. Graduated in Computer Engineering from the Federal University of Bahia in 2017, including a sandwich year in Canada at the University of Alberta, with 3 months of research under Prof. Dr. Michael Bowling. After graduation, Diedre worked as a Computer Engineer at ATON Engenharia, applying Computer Vision knowledge to improve and deploy state-of-the-art algorithms into existing vision based smoke and fire detection systems. His master's degree (2018-2020) with a full time FAPESP scholarship was at UNICAMP, applying Deep Learning to hippocampus segmentation, under the guidance of professors Roberto Lotufo and Letícia Rittner. Currently working full time on his PhD, under the same supervision, using deep learning for automatic segmentation and quantification of structures and findings in CT images of the lung. (Source: Lattes Curriculum)

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Scientific publications resulting from Research Grants and Scholarships under the grantee's responsibility (2)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

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CARMO, DIEDRE; SILVA, BRUNA; YASUDA, CLARISSA; RITTNER, LETICIA; LOTUFO, ROBERTO; NEUROIMAGING, ALZHEIMER'S DIS. Hippocampus segmentation on epilepsy and Alzheimer's disease studies with multiple convolutional neural networks. HELIYON, v. 7, n. 2, . Web of Science Citations: 0. (18/00186-0)

CARMO, DIEDRE; CAMPIOTTI, ISRAEL; RODRIGUES, LIVIA; FANTINI, IRENE; PINHEIRO, GUSTAVO; MORAES, DANIEL; NOGUEIRA, RODRIGO; RITTNER, LETICIA; LOTUFO, ROBERTO. Rapidly deploying a COVID-19 decision support system in one of the largest Brazilian hospitals. HEALTH INFORMATICS JOURNAL, v. 27, n. 3, . Web of Science Citations: 0. (13/07559-3, 19/21964-4)

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