文献
J-GLOBAL ID:202202266910522786
整理番号:22A1181113
急性冠症候群罹患率の予測における効果的な手段としての機械学習解析気象条件【JST・京大機械翻訳】
Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence
著者 (7件):
Wlodarczyk Aleksandra
(Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, John Paul II Hospital, Krakow, Poland)
,
Molek Patrycja
(Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, John Paul II Hospital, Krakow, Poland)
,
Bochenek Bogdan
(Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland)
,
Wypych Agnieszka
(Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland)
,
Wypych Agnieszka
(Department of Climatology, Jagiellonian University, Krakow, Poland)
,
Nessler Jadwiga
(Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, John Paul II Hospital, Krakow, Poland)
,
Zalewski Jaroslaw
(Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, John Paul II Hospital, Krakow, Poland)
資料名:
Frontiers in Cardiovascular Medicine (Web)
(Frontiers in Cardiovascular Medicine (Web))
巻:
9
ページ:
830823
発行年:
2022年
JST資料番号:
U7061A
ISSN:
2297-055X
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
スイス (CHE)
言語:
英語 (EN)