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pro vyhledávání: '"Kaoru Shimada-Sammori"'
Machine learning algorithms for predicting days of high incidence for out-of-hospital cardiac arrest
Autor:
Kaoru Shimada-Sammori, Tadanaga Shimada, Rie E. Miura, Rui Kawaguchi, Yasuo Yamao, Taku Oshima, Takehiko Oami, Keisuke Tomita, Koichiro Shinozaki, Taka-aki Nakada
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract Predicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA incidences. We used the Japanese population
Externí odkaz:
https://doaj.org/article/06db531055b84a178b9099bfada32b25
Autor:
Kaoru Shimada-Sammori, Tadanaga Shimada, Rie E. Miura, Rui Kawaguchi, Yasuo Yamao, Taku Oshima, Takehiko Oami, Keisuke Tomita, Koichiro Shinozaki, Taka-aki Nakada
Background: Predicting out-of-hospital cardiac arrest (OHCA) events might contribute to the improvement of OHCA patients’ outcomes. We hypothesized that machine learning algorithms using meteorological and chronological information would predict hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a36d7b5831dc083205512faf8eeafc6
https://doi.org/10.21203/rs.3.rs-1903729/v1
https://doi.org/10.21203/rs.3.rs-1903729/v1