Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data

Takahiro Nakashima,Satoshi Kato,Teruo Noguchi,Yoshio Tahara,Hiroshi Nonogi,Robert Neumar,Daisuke Onozuka,Ken Nagao,Soshiro Ogata,Sunao Kojima,Yoshiki Yamagata,Koji Iihara,Taku Iwami,Tetsuya Sakamoto,Satoshi Yasuda,Kunihiro Nishimura

doi:10.1136/heartjnl-2020-318726

Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data

Takahiro Nakashima, Satoshi Kato + Show 14 more

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https://doi.org/10.1136/heartjnl-2020-318726

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Journal: Heart	Publication Date: Jun 11, 2021
Citations: 26	License type: open-access

Affiliation: National Cerebral and Cardiovascular Center, University of Michigan–Ann Arbor, Shizuoka General Hospital, Nihon University, Kawasaki Medical School, National Institute for Environmental Studies, Kyoto University, Teikyo University, Tohoku University

#Mean Absolute Error #Out-of-hospital Cardiac Arrest #Mean Absolute Percentage Error #Out-of-hospital Cardiac Arrest Incidence #Training Dataset #Out-of-hospital Cardiac Arrest Cases #Chronological Data #Machine Learning Model #Machine Learning Predictive Model #Machine Learning

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ObjectivesTo evaluate a predictive model for robust estimation of daily out-of-hospital cardiac arrest (OHCA) incidence using a suite of machine learning (ML) approaches and high-resolution meteorological and chronological data.MethodsIn this...

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Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data