YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos
This addresses the need for scalable algorithmic solutions to improve healthcare information dissemination for patients, though it appears incremental in applying existing deep learning techniques to a new domain.
The researchers tackled the problem of evaluating YouTube videos for health literacy and patient education by developing a deep learning method to extract and classify medical knowledge from user-generated videos, achieving satisfying performance in preliminary results.
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.