Hussain, Zain U.

Mukherjee, Mome

Shah, Syed Ahmar

Sheikh, Aziz

English

Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at high risk of asthma attacks in primary care by leveraging advances in machine learning

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Predicting the risk of asthma attacks in children, adolescents and adults:protocol for a machine learning algorithm derived from a primary care-based retrospective cohort

https://www.pure.ed.ac.uk/ws/files/157681268/Predicting_the_risk_of_asthma_attacks_using_machine_learning_protocol.pdf

Predicting the risk of asthma attacks in children, adolescents and adults:protocol for a machine learning algorithm derived from a primary care-based retrospective cohort

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