Sunday, July 22, 2018

Machine Learning Predicts Clinical Deterioration

Edelson and her colleagues trained a gradient boosted machine model on a dataset of almost 300K patients and were able to predict clinical deterioration better than the modified early warning (MEWS) system. Here is the link for the abstract that was presented at ATS 2018.

The simplicity of the tool which uses only age, heart rate, and respiratory is really impressive. Interestingly, respiratory rate is often the least accurately measured vital sign in the hospitals despite its simplicity. A more accurate measurement of respiratory rate can potentially help better predictive models to predict clinical worsening in a patient’s condition. Better prediction can not only help to patients by focusing on the cause of clinical worsening but will also help to more optimally utilize resources within the hospital.

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