  YouTube presents an unprecedented opportunity to explore how machine learning
methods can improve healthcare information dissemination. We propose an
interdisciplinary lens that synthesizes machine learning methods with
healthcare informatics themes to address the critical issue of developing a
scalable algorithmic solution to evaluate videos from a health literacy and
patient education perspective. We develop a deep learning method to understand
the level of medical knowledge encoded in YouTube videos. Preliminary results
suggest that we can extract medical knowledge from YouTube videos and classify
videos according to the embedded knowledge with satisfying performance. Deep
learning methods show great promise in knowledge extraction, natural language
understanding, and image classification, especially in an era of
patient-centric care and precision medicine.
