The tool takes data from six patient vital readings and synthesizes it into one of four separate clusters that clinicians can use to understand a patient’s likely medical outcomes. This gives clinicians an idea of which patients are likely to deteriorate and require further intervention.
The algorithm was tested on the deidentified data of 100,000 patients who were admitted into Gainesville-based UF Health Shands Hospital from 2014 to 2016, according to an Oct. 19 University of Florida news release.
Researchers are now looking for more grant funding to test the algorithm on current hospital patients.
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