If you have been paying attention to data science in healthcare you will have noticed the gradual shift from 2016’s Big Data to 2017’s Machine Learning. Specifically, deep learning techniques attract much of the attention. The FDA recently approved the use of deep learning techniques in cardiac diagnoses. Enlitic promises to automate the process of radiologic diagnosis for medical imaging. And with the advent of wearables, there is an ever-increasing volume of health data that requires “smart” algorithms to parse out the signal from the noise. Continue reading