Machine Learning for Data-Driven Discovery: The Rise and Relevance

Partho P Sengupta, Sirish Shrestha, Partho P Sengupta, Sirish Shrestha

No abstract available

Keywords: echocardiography; electronic health records; machine learning; mortality.

Figures

FIGURE 1. The Growth of Machine Learning Techniques for Cardiac Imaging

The data was collected using R package RISmed (6) to retrieve the publication data on cardiology imaging from PubMed between 1998 and 2017. (A) Cumulative usage of machine learning techniques in cardiac imaging publications (cardiac computed tomography, cardiac perfusion single-photon emission computed tomography or nuclear cardiology, echocardiography, and cardiac magnetic resonance imaging) from 1998 to 2017. (B) Cumulative publication counts for individual algorithm used in echocardiography from 1998 to 2017. Recently, interest in random forest has peaked, while SVM has plateaued. *Query for neural networks contains the keywords “artificial neural network,” “deep neural network,” and “deep learning.”