How to help save lives using AI

▤ Summary

SAS hosted a Virtual Data Science Experience Day,where it presented how machine learning is used to reduce the risk of heart attacks by predicting stent failure. Understanding and being able to predict the main drivers of stent device failure using advanced algorithms allows us to continuously improve the treatment and patient safety. We will be using analytical software to create a visual report and compare several supervised machine learning algorithms such as logistic regression, gradient boosting and neural networks. From this decision tree, we can see a misclassification rate of 0.1896 – which means that this model can accurately predict around 81 per cent of cases which lead to stent failure. You can perform your data mining via Python or R, and then apply the machine learning techniques, or you could create an entire process in open source and compare it against the SAS models to pick the best one.

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SAS

$1M to $5M