AI methods predict COVID-19 patient outcomes using routine clinical data from ICUs
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
While the AI model was used on a retrospective cohort of patient data collected during the pandemic s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.
The researchers say the approach, where each patient s data were analyzed day-by-day instead of only on admission, could be used to improve guidelines in clinical practice going forward. It could be applied to potential future waves of the pandemic and other diseases treated in similar clinical settings.
Date Time
AI analytics predict COVID-19 patients’ daily trajectory in UK intensive care
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill COVID-19 patients.
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) – a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works. Dr Brijesh Patel
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The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
While the AI model was used on a retrospective cohort of patient data collected during the pandemic s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.
The researchers say the approach, where each patient s data were analysed day-by-day instead of only on admission, could be used to improve guidelines in clinical practice going forward. It could be applied to potential future waves of the pandemic and other diseases treated in similar clinical settings.
11 May 2021
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill COVID-19 patients.
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) – a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works. Dr Brijesh Patel Department of Surgery and Cancer
While the AI model was used on a retrospective cohort of patient data collected during the pandemic’s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.