Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Styve Pamphile"'
Autor:
Hiroyuki Shimizu, Brendan J. Barrett, Koh Okamoto, Akihiro Ueda, Kazutoshi Iijima, Shigeru Mikami, Ayumu Tsubosaka, Kansei Watanabe, Hideaki Kato, Fan Yang, Makoto Yabe, Natsuo Tachikawa, Bohua Ma, Kazuki Taoka, Yohei Doi, Sakura Davis, Kazuyoshi Kurashima, Kyoji Moriya, Mai Takematsu, Ikura Hashimoto, Shota Sugiyama, Hiroki Ienaga, Yasushi Shibue, Sohei Harada, Yusuke Yoshino, Styve Pamphile, Masao Hagihara, Masaki Ishihara, Saki Namura, Eiki Shoji, Hideaki Nakajima
Publikováno v:
SSRN Electronic Journal.
Background: It has been difficult to distinguish between mild, moderate, and severe cases at an early stage for COVID-19 patients, making it challenging to decide an optimized treatment for each patient. This machine learning system could predict the
Autor:
Yael Jessica Mayer, Sabrina Fowler, Fan Yang, Benjamin W. Friedman, Jinsung Kim, Carly Bass, Maykl Mosheyev, Styve Pamphile, Shira Yellin, Farnia Naeem, Rachel Borczuk, Jayabhargav Annam, Brendan J. Barrett
Publikováno v:
The American Journal of Emergency Medicine
Background Inflammatory markers are often elevated in patients with COVID-19. The objective of this study is to assess the prognostic capability of these tests in predicting clinical outcomes. Methods This was a retrospective cohort study including a
Publikováno v:
Annals of Emergency Medicine
Study Objectives: For several weeks in March and April 2020, New York City was the global epicenter of the COVID-19 outbreak Minority populations in the Bronx were disproportionately affected Clinical practice changed significantly, with clinicians o