A machine learning approach for identifying patients with cardiac amyloidosis

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Machine Learning

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A machine learning approach for identifying patients with cardiac amyloidosis

A Bootstrap Machine Learning Approach to Identify Rare Disease Patients from Electronic Health Records

In this paper, we aim to automate the process of identifying potential cardiac amyloidosis patients with the help of machine learning algorithms and also learn most predictive factors.

We achieved high average cross-validation cross-validation score of 0.98 using an ensemble machine learning classifier.

Authors

Ravi Garg, Shu Dong, Sanjiv Shah, Siddhartha R Jonnalagadda

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