KOICHI SAMESHIMA

(Fonte: Lattes)
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Departamento de Radiologia, Faculdade de Medicina - Docente
LIM/43 - Laboratório de Medicina Nuclear, Hospital das Clínicas, Faculdade de Medicina - Líder

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Agora exibindo 1 - 3 de 3
  • article 6 Citação(ões) na Scopus
    Partial directed coherence: twenty years on some history and an appraisal
    (2021) BACCALA, Luiz A.; SAMESHIMA, Koichi
    Here while we reminisce about how partial directed coherence was proposed, its motivation and evolution, we take the opportunity to relate it to some of its kin quantities and some of its offspring. Emphasis is placed on our development of asymptotic criteria to place it as a reliable investigation tool, where the connectivity detection problem is completely solved as opposed to what we call the characterization problem. We end by musing over some points now on our wishlist.
  • conferenceObject
    Deep learning algorithm performance in mammography screening: A systematic review and meta-analysis.
    (2021) ROELA, Rosimeire Aparecida; VALENTE, Gabriel Vansuita; SHIMIZU, Carlos; LOPEZ, Rossana Veronica Mendoza; TUCUNDUVA, Tatiana Cardoso de Mello; FOLGUEIRA, Guilherme Koike; KATAYAMA, Maria Lucia Hirata; PETRINI, Daniel Gustavo Pellacani; NOVAES, Guilherme Apolinario Silva; SERIO, Pedro Adolpho de Menezes Pacheco; MARTA, Guilherme Nader; SAMESHIMA, Koichi; KIM, Hae Yong; FOLGUEIRA, Maria A. A. Koike
  • article 6 Citação(ões) na Scopus
    Frequency Domain Repercussions of Instantaneous Granger Causality
    (2021) BACCALA, Luiz A.; SAMESHIMA, Koichi
    Using directed transfer function (DTF) and partial directed coherence (PDC) in the information version, this paper extends the theoretical framework to incorporate the instantaneous Granger causality (iGC) frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC's repercussions associated with Granger connectivity, where interactions mediated without delay between time series can be easily detected.