According to a recent survey in US hospitals, the rate of adult patient readmission within 30 days of discharge is 14.9% and is growing year after year. So, it has become a difficult task for the hospitals to identify the possibility of readmission, and to overcome this issue we have used a Machine Learning Model that helps in predicting the possibilities based on the historical data.
In this video, we will showcase how we have built the Machine Learning model (Naive Bayes) that identifies the readmission of patients through their data which is statistically computed using R and Shiny. Also, our experts will discuss various approaches for better understanding of readmissions.
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